Overview

Dataset statistics

Number of variables134
Number of observations4920
Missing cells4920
Missing cells (%)0.7%
Duplicate rows304
Duplicate rows (%)6.2%
Total size in memory5.3 MiB
Average record size in memory1.1 KiB

Variable types

Categorical133
Unsupported1

Alerts

fluid_overload has constant value ""Constant
Dataset has 304 (6.2%) duplicate rowsDuplicates
abdominal_pain is highly overall correlated with dark_urine and 3 other fieldsHigh correlation
abnormal_menstruation is highly overall correlated with brittle_nails and 8 other fieldsHigh correlation
acidity is highly overall correlated with prognosis and 2 other fieldsHigh correlation
acute_liver_failure is highly overall correlated with coma and 2 other fieldsHigh correlation
altered_sensorium is highly overall correlated with prognosis and 1 other fieldsHigh correlation
anxiety is highly overall correlated with blurred_and_distorted_vision and 4 other fieldsHigh correlation
back_pain is highly overall correlated with pain_behind_the_eyes and 2 other fieldsHigh correlation
belly_pain is highly overall correlated with constipation and 2 other fieldsHigh correlation
blackheads is highly overall correlated with prognosis and 2 other fieldsHigh correlation
bladder_discomfort is highly overall correlated with burning_micturition and 3 other fieldsHigh correlation
blister is highly overall correlated with prognosis and 2 other fieldsHigh correlation
blood_in_sputum is highly overall correlated with mild_fever and 3 other fieldsHigh correlation
bloody_stool is highly overall correlated with constipation and 4 other fieldsHigh correlation
blurred_and_distorted_vision is highly overall correlated with anxiety and 10 other fieldsHigh correlation
breathlessness is highly overall correlated with chest_pain and 4 other fieldsHigh correlation
brittle_nails is highly overall correlated with abnormal_menstruation and 9 other fieldsHigh correlation
bruising is highly overall correlated with cramps and 5 other fieldsHigh correlation
burning_micturition is highly overall correlated with bladder_discomfort and 4 other fieldsHigh correlation
chest_pain is highly overall correlated with breathlessness and 3 other fieldsHigh correlation
chills is highly overall correlated with high_fever and 3 other fieldsHigh correlation
cold_hands_and_feets is highly overall correlated with abnormal_menstruation and 9 other fieldsHigh correlation
coma is highly overall correlated with acute_liver_failure and 2 other fieldsHigh correlation
congestion is highly overall correlated with continuous_sneezing and 8 other fieldsHigh correlation
constipation is highly overall correlated with belly_pain and 6 other fieldsHigh correlation
continuous_feel_of_urine is highly overall correlated with bladder_discomfort and 3 other fieldsHigh correlation
continuous_sneezing is highly overall correlated with congestion and 8 other fieldsHigh correlation
cough is highly overall correlated with breathlessness and 3 other fieldsHigh correlation
cramps is highly overall correlated with bruising and 5 other fieldsHigh correlation
dark_urine is highly overall correlated with abdominal_pain and 3 other fieldsHigh correlation
dehydration is highly overall correlated with prognosis and 1 other fieldsHigh correlation
depression is highly overall correlated with brittle_nails and 8 other fieldsHigh correlation
diarrhoea is highly overall correlated with prognosisHigh correlation
dischromic _patches is highly overall correlated with nodal_skin_eruptions and 1 other fieldsHigh correlation
distention_of_abdomen is highly overall correlated with fluid_overload.1 and 3 other fieldsHigh correlation
dizziness is highly overall correlated with brittle_nails and 9 other fieldsHigh correlation
drying_and_tingling_lips is highly overall correlated with anxiety and 4 other fieldsHigh correlation
enlarged_thyroid is highly overall correlated with abnormal_menstruation and 9 other fieldsHigh correlation
excessive_hunger is highly overall correlated with blurred_and_distorted_vision and 3 other fieldsHigh correlation
extra_marital_contacts is highly overall correlated with muscle_wasting and 2 other fieldsHigh correlation
family_history is highly overall correlated with mucoid_sputum and 1 other fieldsHigh correlation
fast_heart_rate is highly overall correlated with prognosis and 2 other fieldsHigh correlation
fatigue is highly overall correlated with prognosisHigh correlation
fluid_overload.1 is highly overall correlated with distention_of_abdomen and 3 other fieldsHigh correlation
foul_smell_of urine is highly overall correlated with bladder_discomfort and 3 other fieldsHigh correlation
headache is highly overall correlated with prognosisHigh correlation
high_fever is highly overall correlated with chills and 1 other fieldsHigh correlation
hip_joint_pain is highly overall correlated with knee_pain and 4 other fieldsHigh correlation
history_of_alcohol_consumption is highly overall correlated with distention_of_abdomen and 3 other fieldsHigh correlation
increased_appetite is highly overall correlated with blurred_and_distorted_vision and 5 other fieldsHigh correlation
indigestion is highly overall correlated with internal_itching and 3 other fieldsHigh correlation
inflammatory_nails is highly overall correlated with prognosis and 3 other fieldsHigh correlation
internal_itching is highly overall correlated with indigestion and 2 other fieldsHigh correlation
irregular_sugar_level is highly overall correlated with blurred_and_distorted_vision and 5 other fieldsHigh correlation
irritability is highly overall correlated with abnormal_menstruation and 5 other fieldsHigh correlation
irritation_in_anus is highly overall correlated with bloody_stool and 4 other fieldsHigh correlation
itching is highly overall correlated with prognosisHigh correlation
joint_pain is highly overall correlated with prognosisHigh correlation
knee_pain is highly overall correlated with hip_joint_pain and 4 other fieldsHigh correlation
lack_of_concentration is highly overall correlated with dizziness and 2 other fieldsHigh correlation
lethargy is highly overall correlated with prognosisHigh correlation
loss_of_appetite is highly overall correlated with prognosis and 2 other fieldsHigh correlation
loss_of_balance is highly overall correlated with dizziness and 5 other fieldsHigh correlation
loss_of_smell is highly overall correlated with congestion and 8 other fieldsHigh correlation
malaise is highly overall correlated with chills and 4 other fieldsHigh correlation
mild_fever is highly overall correlated with blood_in_sputum and 2 other fieldsHigh correlation
mood_swings is highly overall correlated with abnormal_menstruation and 8 other fieldsHigh correlation
movement_stiffness is highly overall correlated with muscle_weakness and 4 other fieldsHigh correlation
mucoid_sputum is highly overall correlated with family_history and 1 other fieldsHigh correlation
muscle_pain is highly overall correlated with prognosisHigh correlation
muscle_wasting is highly overall correlated with extra_marital_contacts and 2 other fieldsHigh correlation
muscle_weakness is highly overall correlated with movement_stiffness and 1 other fieldsHigh correlation
nausea is highly overall correlated with prognosis and 1 other fieldsHigh correlation
neck_pain is highly overall correlated with hip_joint_pain and 3 other fieldsHigh correlation
nodal_skin_eruptions is highly overall correlated with dischromic _patches and 1 other fieldsHigh correlation
obesity is highly overall correlated with bruising and 8 other fieldsHigh correlation
pain_behind_the_eyes is highly overall correlated with back_pain and 2 other fieldsHigh correlation
pain_during_bowel_movements is highly overall correlated with bloody_stool and 4 other fieldsHigh correlation
pain_in_anal_region is highly overall correlated with bloody_stool and 4 other fieldsHigh correlation
painful_walking is highly overall correlated with hip_joint_pain and 4 other fieldsHigh correlation
palpitations is highly overall correlated with anxiety and 4 other fieldsHigh correlation
passage_of_gases is highly overall correlated with indigestion and 2 other fieldsHigh correlation
patches_in_throat is highly overall correlated with extra_marital_contacts and 2 other fieldsHigh correlation
phlegm is highly overall correlated with blood_in_sputum and 14 other fieldsHigh correlation
polyuria is highly overall correlated with blurred_and_distorted_vision and 5 other fieldsHigh correlation
prognosis is highly overall correlated with abdominal_pain and 130 other fieldsHigh correlation
prominent_veins_on_calf is highly overall correlated with bruising and 5 other fieldsHigh correlation
puffy_face_and_eyes is highly overall correlated with abnormal_menstruation and 9 other fieldsHigh correlation
pus_filled_pimples is highly overall correlated with blackheads and 2 other fieldsHigh correlation
receiving_blood_transfusion is highly overall correlated with prognosis and 2 other fieldsHigh correlation
receiving_unsterile_injections is highly overall correlated with prognosis and 2 other fieldsHigh correlation
red_sore_around_nose is highly overall correlated with blister and 2 other fieldsHigh correlation
red_spots_over_body is highly overall correlated with malaise and 2 other fieldsHigh correlation
redness_of_eyes is highly overall correlated with congestion and 8 other fieldsHigh correlation
restlessness is highly overall correlated with excessive_hunger and 5 other fieldsHigh correlation
runny_nose is highly overall correlated with congestion and 8 other fieldsHigh correlation
rusty_sputum is highly overall correlated with fast_heart_rate and 2 other fieldsHigh correlation
scurring is highly overall correlated with blackheads and 2 other fieldsHigh correlation
shivering is highly overall correlated with continuous_sneezing and 2 other fieldsHigh correlation
silver_like_dusting is highly overall correlated with inflammatory_nails and 3 other fieldsHigh correlation
sinus_pressure is highly overall correlated with congestion and 8 other fieldsHigh correlation
skin_peeling is highly overall correlated with inflammatory_nails and 3 other fieldsHigh correlation
skin_rash is highly overall correlated with prognosisHigh correlation
slurred_speech is highly overall correlated with anxiety and 4 other fieldsHigh correlation
small_dents_in_nails is highly overall correlated with inflammatory_nails and 3 other fieldsHigh correlation
spinning_movements is highly overall correlated with loss_of_balance and 2 other fieldsHigh correlation
spotting_ urination is highly overall correlated with burning_micturition and 2 other fieldsHigh correlation
stiff_neck is highly overall correlated with movement_stiffness and 2 other fieldsHigh correlation
stomach_bleeding is highly overall correlated with acute_liver_failure and 2 other fieldsHigh correlation
stomach_pain is highly overall correlated with prognosis and 2 other fieldsHigh correlation
sunken_eyes is highly overall correlated with dehydration and 1 other fieldsHigh correlation
sweating is highly overall correlated with breathlessness and 2 other fieldsHigh correlation
swelled_lymph_nodes is highly overall correlated with blood_in_sputum and 10 other fieldsHigh correlation
swelling_joints is highly overall correlated with hip_joint_pain and 4 other fieldsHigh correlation
swelling_of_stomach is highly overall correlated with distention_of_abdomen and 3 other fieldsHigh correlation
swollen_blood_vessels is highly overall correlated with bruising and 5 other fieldsHigh correlation
swollen_extremeties is highly overall correlated with abnormal_menstruation and 9 other fieldsHigh correlation
swollen_legs is highly overall correlated with bruising and 5 other fieldsHigh correlation
throat_irritation is highly overall correlated with congestion and 8 other fieldsHigh correlation
toxic_look_(typhos) is highly overall correlated with belly_pain and 2 other fieldsHigh correlation
ulcers_on_tongue is highly overall correlated with acidity and 2 other fieldsHigh correlation
unsteadiness is highly overall correlated with loss_of_balance and 2 other fieldsHigh correlation
visual_disturbances is highly overall correlated with acidity and 5 other fieldsHigh correlation
vomiting is highly overall correlated with nausea and 1 other fieldsHigh correlation
watering_from_eyes is highly overall correlated with continuous_sneezing and 2 other fieldsHigh correlation
weakness_in_limbs is highly overall correlated with back_pain and 4 other fieldsHigh correlation
weakness_of_one_body_side is highly overall correlated with altered_sensorium and 1 other fieldsHigh correlation
weight_gain is highly overall correlated with abnormal_menstruation and 9 other fieldsHigh correlation
weight_loss is highly overall correlated with prognosis and 1 other fieldsHigh correlation
yellow_crust_ooze is highly overall correlated with blister and 2 other fieldsHigh correlation
yellow_urine is highly overall correlated with prognosis and 2 other fieldsHigh correlation
yellowing_of_eyes is highly overall correlated with abdominal_pain and 4 other fieldsHigh correlation
yellowish_skin is highly overall correlated with abdominal_pain and 4 other fieldsHigh correlation
nodal_skin_eruptions is highly imbalanced (84.8%)Imbalance
continuous_sneezing is highly imbalanced (73.5%)Imbalance
shivering is highly imbalanced (84.8%)Imbalance
stomach_pain is highly imbalanced (73.5%)Imbalance
acidity is highly imbalanced (73.5%)Imbalance
ulcers_on_tongue is highly imbalanced (84.8%)Imbalance
muscle_wasting is highly imbalanced (84.8%)Imbalance
burning_micturition is highly imbalanced (74.0%)Imbalance
spotting_ urination is highly imbalanced (84.8%)Imbalance
weight_gain is highly imbalanced (84.1%)Imbalance
anxiety is highly imbalanced (84.1%)Imbalance
cold_hands_and_feets is highly imbalanced (84.1%)Imbalance
mood_swings is highly imbalanced (72.9%)Imbalance
weight_loss is highly imbalanced (55.5%)Imbalance
restlessness is highly imbalanced (72.9%)Imbalance
lethargy is highly imbalanced (55.5%)Imbalance
patches_in_throat is highly imbalanced (84.8%)Imbalance
irregular_sugar_level is highly imbalanced (84.1%)Imbalance
sunken_eyes is highly imbalanced (84.8%)Imbalance
breathlessness is highly imbalanced (55.9%)Imbalance
dehydration is highly imbalanced (84.8%)Imbalance
indigestion is highly imbalanced (73.5%)Imbalance
pain_behind_the_eyes is highly imbalanced (83.5%)Imbalance
back_pain is highly imbalanced (72.9%)Imbalance
constipation is highly imbalanced (72.9%)Imbalance
mild_fever is highly imbalanced (62.7%)Imbalance
yellow_urine is highly imbalanced (84.1%)Imbalance
acute_liver_failure is highly imbalanced (84.1%)Imbalance
swelling_of_stomach is highly imbalanced (84.1%)Imbalance
swelled_lymph_nodes is highly imbalanced (63.1%)Imbalance
blurred_and_distorted_vision is highly imbalanced (63.6%)Imbalance
phlegm is highly imbalanced (62.7%)Imbalance
throat_irritation is highly imbalanced (83.5%)Imbalance
redness_of_eyes is highly imbalanced (83.5%)Imbalance
sinus_pressure is highly imbalanced (83.5%)Imbalance
runny_nose is highly imbalanced (83.5%)Imbalance
congestion is highly imbalanced (83.5%)Imbalance
weakness_in_limbs is highly imbalanced (84.8%)Imbalance
fast_heart_rate is highly imbalanced (72.4%)Imbalance
pain_during_bowel_movements is highly imbalanced (84.1%)Imbalance
pain_in_anal_region is highly imbalanced (84.1%)Imbalance
bloody_stool is highly imbalanced (84.1%)Imbalance
irritation_in_anus is highly imbalanced (84.1%)Imbalance
neck_pain is highly imbalanced (72.9%)Imbalance
dizziness is highly imbalanced (64.0%)Imbalance
cramps is highly imbalanced (84.1%)Imbalance
bruising is highly imbalanced (84.1%)Imbalance
obesity is highly imbalanced (72.9%)Imbalance
swollen_legs is highly imbalanced (84.1%)Imbalance
swollen_blood_vessels is highly imbalanced (84.8%)Imbalance
puffy_face_and_eyes is highly imbalanced (84.1%)Imbalance
enlarged_thyroid is highly imbalanced (83.5%)Imbalance
brittle_nails is highly imbalanced (83.5%)Imbalance
swollen_extremeties is highly imbalanced (83.5%)Imbalance
excessive_hunger is highly imbalanced (55.1%)Imbalance
extra_marital_contacts is highly imbalanced (84.8%)Imbalance
drying_and_tingling_lips is highly imbalanced (84.1%)Imbalance
slurred_speech is highly imbalanced (83.5%)Imbalance
knee_pain is highly imbalanced (84.1%)Imbalance
hip_joint_pain is highly imbalanced (84.1%)Imbalance
muscle_weakness is highly imbalanced (72.4%)Imbalance
stiff_neck is highly imbalanced (72.9%)Imbalance
swelling_joints is highly imbalanced (72.9%)Imbalance
movement_stiffness is highly imbalanced (84.1%)Imbalance
spinning_movements is highly imbalanced (84.8%)Imbalance
loss_of_balance is highly imbalanced (63.6%)Imbalance
unsteadiness is highly imbalanced (84.1%)Imbalance
weakness_of_one_body_side is highly imbalanced (84.8%)Imbalance
loss_of_smell is highly imbalanced (83.5%)Imbalance
bladder_discomfort is highly imbalanced (84.1%)Imbalance
foul_smell_of urine is highly imbalanced (85.4%)Imbalance
continuous_feel_of_urine is highly imbalanced (84.1%)Imbalance
passage_of_gases is highly imbalanced (84.1%)Imbalance
internal_itching is highly imbalanced (84.1%)Imbalance
toxic_look_(typhos) is highly imbalanced (84.1%)Imbalance
depression is highly imbalanced (72.4%)Imbalance
irritability is highly imbalanced (54.3%)Imbalance
muscle_pain is highly imbalanced (54.3%)Imbalance
altered_sensorium is highly imbalanced (84.1%)Imbalance
red_spots_over_body is highly imbalanced (72.4%)Imbalance
belly_pain is highly imbalanced (84.1%)Imbalance
abnormal_menstruation is highly imbalanced (71.9%)Imbalance
dischromic _patches is highly imbalanced (84.8%)Imbalance
watering_from_eyes is highly imbalanced (84.8%)Imbalance
increased_appetite is highly imbalanced (83.5%)Imbalance
polyuria is highly imbalanced (83.5%)Imbalance
family_history is highly imbalanced (72.9%)Imbalance
mucoid_sputum is highly imbalanced (84.1%)Imbalance
rusty_sputum is highly imbalanced (83.5%)Imbalance
lack_of_concentration is highly imbalanced (84.1%)Imbalance
visual_disturbances is highly imbalanced (84.1%)Imbalance
receiving_blood_transfusion is highly imbalanced (83.5%)Imbalance
receiving_unsterile_injections is highly imbalanced (83.5%)Imbalance
coma is highly imbalanced (83.5%)Imbalance
stomach_bleeding is highly imbalanced (83.5%)Imbalance
distention_of_abdomen is highly imbalanced (84.1%)Imbalance
history_of_alcohol_consumption is highly imbalanced (84.1%)Imbalance
fluid_overload.1 is highly imbalanced (84.1%)Imbalance
blood_in_sputum is highly imbalanced (83.5%)Imbalance
prominent_veins_on_calf is highly imbalanced (84.1%)Imbalance
palpitations is highly imbalanced (83.5%)Imbalance
painful_walking is highly imbalanced (72.9%)Imbalance
pus_filled_pimples is highly imbalanced (84.8%)Imbalance
blackheads is highly imbalanced (84.8%)Imbalance
scurring is highly imbalanced (84.8%)Imbalance
skin_peeling is highly imbalanced (84.1%)Imbalance
silver_like_dusting is highly imbalanced (84.1%)Imbalance
small_dents_in_nails is highly imbalanced (84.1%)Imbalance
inflammatory_nails is highly imbalanced (84.1%)Imbalance
blister is highly imbalanced (84.1%)Imbalance
red_sore_around_nose is highly imbalanced (84.1%)Imbalance
yellow_crust_ooze is highly imbalanced (84.1%)Imbalance
Unnamed: 133 has 4920 (100.0%) missing valuesMissing
prognosis is uniformly distributedUniform
Unnamed: 133 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-22 01:00:33.564877
Analysis finished2024-01-22 01:00:57.257445
Duration23.69 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

itching
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4242 
1
678 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Length

2024-01-22T12:00:57.305038image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:57.370274image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Most occurring characters

ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

skin_rash
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4134 
1
786 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 4134
84.0%
1 786
 
16.0%

Length

2024-01-22T12:00:57.436587image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:57.496930image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4134
84.0%
1 786
 
16.0%

Most occurring characters

ValueCountFrequency (%)
0 4134
84.0%
1 786
 
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4134
84.0%
1 786
 
16.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4134
84.0%
1 786
 
16.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4134
84.0%
1 786
 
16.0%

nodal_skin_eruptions
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:00:57.562534image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:57.620108image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

continuous_sneezing
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Length

2024-01-22T12:00:57.683040image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:57.741854image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

shivering
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:00:57.805156image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:57.864416image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

chills
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4122 
1
798 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4122
83.8%
1 798
 
16.2%

Length

2024-01-22T12:00:57.926493image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:57.985152image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4122
83.8%
1 798
 
16.2%

Most occurring characters

ValueCountFrequency (%)
0 4122
83.8%
1 798
 
16.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4122
83.8%
1 798
 
16.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4122
83.8%
1 798
 
16.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4122
83.8%
1 798
 
16.2%

joint_pain
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4236 
1
684 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4236
86.1%
1 684
 
13.9%

Length

2024-01-22T12:00:58.048402image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:58.107585image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4236
86.1%
1 684
 
13.9%

Most occurring characters

ValueCountFrequency (%)
0 4236
86.1%
1 684
 
13.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4236
86.1%
1 684
 
13.9%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4236
86.1%
1 684
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4236
86.1%
1 684
 
13.9%

stomach_pain
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Length

2024-01-22T12:00:58.170996image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:58.229759image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

acidity
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Length

2024-01-22T12:00:58.292364image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:58.350273image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

ulcers_on_tongue
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:00:58.412969image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:58.470617image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

muscle_wasting
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:00:58.532695image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:58.590633image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

vomiting
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
3006 
1
1914 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3006
61.1%
1 1914
38.9%

Length

2024-01-22T12:00:58.653631image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:58.712631image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3006
61.1%
1 1914
38.9%

Most occurring characters

ValueCountFrequency (%)
0 3006
61.1%
1 1914
38.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3006
61.1%
1 1914
38.9%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3006
61.1%
1 1914
38.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3006
61.1%
1 1914
38.9%

burning_micturition
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4704 
1
 
216

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4704
95.6%
1 216
 
4.4%

Length

2024-01-22T12:00:58.777258image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:58.835065image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4704
95.6%
1 216
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 4704
95.6%
1 216
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4704
95.6%
1 216
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4704
95.6%
1 216
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4704
95.6%
1 216
 
4.4%

spotting_ urination
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:00:58.897887image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:58.961963image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

fatigue
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
2988 
1
1932 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2988
60.7%
1 1932
39.3%

Length

2024-01-22T12:00:59.024441image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:59.084036image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2988
60.7%
1 1932
39.3%

Most occurring characters

ValueCountFrequency (%)
0 2988
60.7%
1 1932
39.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2988
60.7%
1 1932
39.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2988
60.7%
1 1932
39.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2988
60.7%
1 1932
39.3%

weight_gain
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:00:59.147691image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:59.205761image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

anxiety
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:00:59.267281image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:59.464438image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

cold_hands_and_feets
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:00:59.526874image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:59.585564image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

mood_swings
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:00:59.647817image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:59.706186image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

weight_loss
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4464 
1
456 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Length

2024-01-22T12:00:59.769576image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:59.827957image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Most occurring characters

ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

restlessness
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:00:59.891656image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:00:59.948842image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

lethargy
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4464 
1
456 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Length

2024-01-22T12:01:00.010907image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:00.068995image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Most occurring characters

ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4464
90.7%
1 456
 
9.3%

patches_in_throat
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:00.132336image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:00.189527image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

irregular_sugar_level
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:00.251497image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:00.309618image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

cough
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4356 
1
564 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Length

2024-01-22T12:01:00.374163image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:00.432138image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Most occurring characters

ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

high_fever
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
3558 
1
1362 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3558
72.3%
1 1362
 
27.7%

Length

2024-01-22T12:01:00.495344image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:00.554821image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3558
72.3%
1 1362
 
27.7%

Most occurring characters

ValueCountFrequency (%)
0 3558
72.3%
1 1362
 
27.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3558
72.3%
1 1362
 
27.7%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3558
72.3%
1 1362
 
27.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3558
72.3%
1 1362
 
27.7%

sunken_eyes
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:00.618392image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:00.676854image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

breathlessness
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4470 
1
450 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4470
90.9%
1 450
 
9.1%

Length

2024-01-22T12:01:00.738286image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:00.797232image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4470
90.9%
1 450
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 4470
90.9%
1 450
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4470
90.9%
1 450
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4470
90.9%
1 450
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4470
90.9%
1 450
 
9.1%

sweating
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4242 
1
678 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Length

2024-01-22T12:01:00.862188image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:00.922239image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Most occurring characters

ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4242
86.2%
1 678
 
13.8%

dehydration
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:00.987351image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:01.046924image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

indigestion
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Length

2024-01-22T12:01:01.111846image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:01.170579image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4698
95.5%
1 222
 
4.5%

headache
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
3786 
1
1134 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3786
77.0%
1 1134
 
23.0%

Length

2024-01-22T12:01:01.233954image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:01.295661image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3786
77.0%
1 1134
 
23.0%

Most occurring characters

ValueCountFrequency (%)
0 3786
77.0%
1 1134
 
23.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3786
77.0%
1 1134
 
23.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3786
77.0%
1 1134
 
23.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3786
77.0%
1 1134
 
23.0%

yellowish_skin
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4008 
1
912 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4008
81.5%
1 912
 
18.5%

Length

2024-01-22T12:01:01.364582image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:01.425469image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4008
81.5%
1 912
 
18.5%

Most occurring characters

ValueCountFrequency (%)
0 4008
81.5%
1 912
 
18.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4008
81.5%
1 912
 
18.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4008
81.5%
1 912
 
18.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4008
81.5%
1 912
 
18.5%

dark_urine
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4350 
1
570 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4350
88.4%
1 570
 
11.6%

Length

2024-01-22T12:01:01.492082image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:01.551716image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4350
88.4%
1 570
 
11.6%

Most occurring characters

ValueCountFrequency (%)
0 4350
88.4%
1 570
 
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4350
88.4%
1 570
 
11.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4350
88.4%
1 570
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4350
88.4%
1 570
 
11.6%

nausea
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
3774 
1
1146 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3774
76.7%
1 1146
 
23.3%

Length

2024-01-22T12:01:01.616428image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:01.676539image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3774
76.7%
1 1146
 
23.3%

Most occurring characters

ValueCountFrequency (%)
0 3774
76.7%
1 1146
 
23.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3774
76.7%
1 1146
 
23.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3774
76.7%
1 1146
 
23.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3774
76.7%
1 1146
 
23.3%

loss_of_appetite
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
3768 
1
1152 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3768
76.6%
1 1152
 
23.4%

Length

2024-01-22T12:01:01.739699image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:01.799398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3768
76.6%
1 1152
 
23.4%

Most occurring characters

ValueCountFrequency (%)
0 3768
76.6%
1 1152
 
23.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3768
76.6%
1 1152
 
23.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3768
76.6%
1 1152
 
23.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3768
76.6%
1 1152
 
23.4%

pain_behind_the_eyes
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:01.864020image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:01.924587image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

back_pain
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:01:01.988894image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:02.049238image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

constipation
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:01:02.112696image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:02.172055image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

abdominal_pain
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
3888 
1
1032 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3888
79.0%
1 1032
 
21.0%

Length

2024-01-22T12:01:02.234948image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:02.294963image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3888
79.0%
1 1032
 
21.0%

Most occurring characters

ValueCountFrequency (%)
0 3888
79.0%
1 1032
 
21.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3888
79.0%
1 1032
 
21.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3888
79.0%
1 1032
 
21.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3888
79.0%
1 1032
 
21.0%

diarrhoea
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4356 
1
564 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Length

2024-01-22T12:01:02.359974image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:02.418950image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Most occurring characters

ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4356
88.5%
1 564
 
11.5%

mild_fever
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4566 
1
 
354

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Length

2024-01-22T12:01:02.483884image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:02.542398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Most occurring characters

ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

yellow_urine
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:02.605517image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:02.663767image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

yellowing_of_eyes
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4104 
1
816 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4104
83.4%
1 816
 
16.6%

Length

2024-01-22T12:01:02.726975image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:02.786100image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4104
83.4%
1 816
 
16.6%

Most occurring characters

ValueCountFrequency (%)
0 4104
83.4%
1 816
 
16.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4104
83.4%
1 816
 
16.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4104
83.4%
1 816
 
16.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4104
83.4%
1 816
 
16.6%

acute_liver_failure
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:02.850462image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:02.912645image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

fluid_overload
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4920 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4920
100.0%

Length

2024-01-22T12:01:02.978886image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:03.037338image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4920
100.0%

Most occurring characters

ValueCountFrequency (%)
0 4920
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4920
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4920
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4920
100.0%

swelling_of_stomach
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:03.098031image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:03.156870image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

swelled_lymph_nodes
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4572 
1
 
348

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4572
92.9%
1 348
 
7.1%

Length

2024-01-22T12:01:03.219649image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:03.278536image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4572
92.9%
1 348
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 4572
92.9%
1 348
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4572
92.9%
1 348
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4572
92.9%
1 348
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4572
92.9%
1 348
 
7.1%

malaise
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4218 
1
702 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4218
85.7%
1 702
 
14.3%

Length

2024-01-22T12:01:03.342542image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:03.401681image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4218
85.7%
1 702
 
14.3%

Most occurring characters

ValueCountFrequency (%)
0 4218
85.7%
1 702
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4218
85.7%
1 702
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4218
85.7%
1 702
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4218
85.7%
1 702
 
14.3%

blurred_and_distorted_vision
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4578 
1
 
342

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Length

2024-01-22T12:01:03.622248image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:03.681713image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Most occurring characters

ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

phlegm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4566 
1
 
354

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Length

2024-01-22T12:01:03.745634image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:03.804345image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Most occurring characters

ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4566
92.8%
1 354
 
7.2%

throat_irritation
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:03.866754image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:03.926292image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

redness_of_eyes
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:03.988885image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:04.051743image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

sinus_pressure
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:04.115105image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:04.174461image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

runny_nose
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:04.236952image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:04.297244image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

congestion
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:04.360742image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:04.419759image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

chest_pain
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4224 
1
696 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4224
85.9%
1 696
 
14.1%

Length

2024-01-22T12:01:04.482566image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:04.541262image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4224
85.9%
1 696
 
14.1%

Most occurring characters

ValueCountFrequency (%)
0 4224
85.9%
1 696
 
14.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4224
85.9%
1 696
 
14.1%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4224
85.9%
1 696
 
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4224
85.9%
1 696
 
14.1%

weakness_in_limbs
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:04.606274image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:04.664714image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

fast_heart_rate
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Length

2024-01-22T12:01:04.728297image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:04.786666image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

pain_during_bowel_movements
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:04.849820image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:04.908106image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

pain_in_anal_region
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:04.970456image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:05.031511image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

bloody_stool
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:05.095327image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:05.154516image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

irritation_in_anus
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:05.217177image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:05.276383image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

neck_pain
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:01:05.338884image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:05.397527image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

dizziness
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4584 
1
 
336

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4584
93.2%
1 336
 
6.8%

Length

2024-01-22T12:01:05.460761image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:05.518713image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4584
93.2%
1 336
 
6.8%

Most occurring characters

ValueCountFrequency (%)
0 4584
93.2%
1 336
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4584
93.2%
1 336
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4584
93.2%
1 336
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4584
93.2%
1 336
 
6.8%

cramps
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:05.582085image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:05.641881image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

bruising
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:05.705652image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:05.763809image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

obesity
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:01:05.826382image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:05.886027image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

swollen_legs
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:05.948699image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:06.008295image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

swollen_blood_vessels
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:06.071182image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:06.129766image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

puffy_face_and_eyes
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:06.193362image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:06.261889image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

enlarged_thyroid
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:06.335258image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:06.395136image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

brittle_nails
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:06.458262image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:06.517147image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

swollen_extremeties
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:06.579939image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:06.639157image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

excessive_hunger
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4458 
1
462 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4458
90.6%
1 462
 
9.4%

Length

2024-01-22T12:01:06.702098image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:06.762170image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4458
90.6%
1 462
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 4458
90.6%
1 462
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4458
90.6%
1 462
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4458
90.6%
1 462
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4458
90.6%
1 462
 
9.4%

extra_marital_contacts
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:06.826579image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:06.885663image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

drying_and_tingling_lips
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:06.949732image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:07.008803image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

slurred_speech
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:07.072385image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:07.131052image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

knee_pain
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:07.194552image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:07.252907image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

hip_joint_pain
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:07.316127image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:07.375713image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

muscle_weakness
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Length

2024-01-22T12:01:07.438514image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:07.497956image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

stiff_neck
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:01:07.560727image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:07.620540image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

swelling_joints
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:01:07.683463image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:07.742172image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

movement_stiffness
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:07.806138image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:07.864781image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

spinning_movements
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:08.068572image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:08.127205image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

loss_of_balance
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4578 
1
 
342

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Length

2024-01-22T12:01:08.190651image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:08.249432image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Most occurring characters

ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4578
93.0%
1 342
 
7.0%

unsteadiness
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:08.312276image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:08.371534image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

weakness_of_one_body_side
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:08.434741image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:08.494348image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

loss_of_smell
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:08.557019image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:08.616887image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

bladder_discomfort
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:08.679868image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:08.739807image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

foul_smell_of urine
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4818 
1
 
102

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4818
97.9%
1 102
 
2.1%

Length

2024-01-22T12:01:08.803161image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:08.862113image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4818
97.9%
1 102
 
2.1%

Most occurring characters

ValueCountFrequency (%)
0 4818
97.9%
1 102
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4818
97.9%
1 102
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4818
97.9%
1 102
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4818
97.9%
1 102
 
2.1%

continuous_feel_of_urine
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:08.927716image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:08.987834image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

passage_of_gases
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:09.051384image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:09.110634image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

internal_itching
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:09.174874image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:09.233544image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

toxic_look_(typhos)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:09.297076image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:09.356343image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

depression
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Length

2024-01-22T12:01:09.419159image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:09.478061image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

irritability
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4446 
1
474 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Length

2024-01-22T12:01:09.540555image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:09.600537image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

muscle_pain
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4446 
1
474 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Length

2024-01-22T12:01:09.664964image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:09.723861image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4446
90.4%
1 474
 
9.6%

altered_sensorium
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:09.788552image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:09.846959image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

red_spots_over_body
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Length

2024-01-22T12:01:09.910295image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:09.968768image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4686
95.2%
1 234
 
4.8%

belly_pain
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:10.032135image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:10.090839image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

abnormal_menstruation
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4680 
1
 
240

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4680
95.1%
1 240
 
4.9%

Length

2024-01-22T12:01:10.153629image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:10.213556image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4680
95.1%
1 240
 
4.9%

Most occurring characters

ValueCountFrequency (%)
0 4680
95.1%
1 240
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4680
95.1%
1 240
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4680
95.1%
1 240
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4680
95.1%
1 240
 
4.9%

dischromic _patches
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:10.276128image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:10.335887image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

watering_from_eyes
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:10.398531image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:10.456851image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

increased_appetite
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:10.522249image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:10.581942image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

polyuria
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:10.645636image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:10.705291image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

family_history
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:01:10.769748image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:10.828292image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

mucoid_sputum
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:10.892235image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:10.952443image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

rusty_sputum
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:11.016145image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:11.077780image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

lack_of_concentration
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:11.140527image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:11.199914image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

visual_disturbances
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:11.263424image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:11.322599image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

receiving_blood_transfusion
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:11.387155image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:11.445422image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

receiving_unsterile_injections
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:11.509940image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:11.569347image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

coma
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:11.632335image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:11.693061image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

stomach_bleeding
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:11.755996image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:11.816591image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

distention_of_abdomen
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:11.880461image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:11.940444image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

history_of_alcohol_consumption
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:12.006243image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:12.065475image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

fluid_overload.1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:12.129092image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:12.187902image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

blood_in_sputum
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:12.251220image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:12.309241image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

prominent_veins_on_calf
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:12.371938image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:12.431057image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

palpitations
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Length

2024-01-22T12:01:12.493240image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:12.696725image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4800
97.6%
1 120
 
2.4%

painful_walking
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Length

2024-01-22T12:01:12.759264image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:12.817451image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4692
95.4%
1 228
 
4.6%

pus_filled_pimples
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:12.880658image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:12.940481image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

blackheads
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:13.006402image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:13.067727image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

scurring
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Length

2024-01-22T12:01:13.132339image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:13.190794image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4812
97.8%
1 108
 
2.2%

skin_peeling
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:13.254241image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:13.312767image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

silver_like_dusting
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:13.376434image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:13.435050image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

small_dents_in_nails
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:13.497396image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:13.556974image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

inflammatory_nails
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:13.619882image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:13.679032image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

blister
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:13.742136image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:13.801620image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

red_sore_around_nose
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:13.863916image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:13.922463image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

yellow_crust_ooze
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size278.8 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4920
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Length

2024-01-22T12:01:13.986415image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-22T12:01:14.045731image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4806
97.7%
1 114
 
2.3%

prognosis
Categorical

HIGH CORRELATION  UNIFORM 

Distinct41
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size337.0 KiB
Fungal infection
 
120
Allergy
 
120
GERD
 
120
Chronic cholestasis
 
120
Drug Reaction
 
120
Other values (36)
4320 

Length

Max length39
Median length16
Mean length13.121951
Min length4

Characters and Unicode

Total characters64560
Distinct characters43
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFungal infection
2nd rowFungal infection
3rd rowFungal infection
4th rowFungal infection
5th rowFungal infection

Common Values

ValueCountFrequency (%)
Fungal infection 120
 
2.4%
Allergy 120
 
2.4%
GERD 120
 
2.4%
Chronic cholestasis 120
 
2.4%
Drug Reaction 120
 
2.4%
Peptic ulcer diseae 120
 
2.4%
AIDS 120
 
2.4%
Diabetes 120
 
2.4%
Gastroenteritis 120
 
2.4%
Bronchial Asthma 120
 
2.4%
Other values (31) 3720
75.6%

Length

2024-01-22T12:01:14.125381image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hepatitis 720
 
9.1%
vertigo 240
 
3.0%
infection 240
 
3.0%
tract 120
 
1.5%
heart 120
 
1.5%
b 120
 
1.5%
c 120
 
1.5%
d 120
 
1.5%
e 120
 
1.5%
alcoholic 120
 
1.5%
Other values (49) 5880
74.2%

Most occurring characters

ValueCountFrequency (%)
i 7440
 
11.5%
e 5160
 
8.0%
t 4680
 
7.2%
a 4440
 
6.9%
s 4440
 
6.9%
o 4320
 
6.7%
r 4080
 
6.3%
3360
 
5.2%
n 2880
 
4.5%
c 2400
 
3.7%
Other values (33) 21360
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 53760
83.3%
Uppercase Letter 6720
 
10.4%
Space Separator 3360
 
5.2%
Close Punctuation 360
 
0.6%
Open Punctuation 360
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 7440
13.8%
e 5160
9.6%
t 4680
 
8.7%
a 4440
 
8.3%
s 4440
 
8.3%
o 4320
 
8.0%
r 4080
 
7.6%
n 2880
 
5.4%
c 2400
 
4.5%
l 2160
 
4.0%
Other values (12) 11760
21.9%
Uppercase Letter
ValueCountFrequency (%)
H 1080
16.1%
D 840
12.5%
A 840
12.5%
C 720
10.7%
P 720
10.7%
V 240
 
3.6%
M 240
 
3.6%
B 240
 
3.6%
T 240
 
3.6%
I 240
 
3.6%
Other values (8) 1320
19.6%
Space Separator
ValueCountFrequency (%)
3360
100.0%
Close Punctuation
ValueCountFrequency (%)
) 360
100.0%
Open Punctuation
ValueCountFrequency (%)
( 360
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60480
93.7%
Common 4080
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 7440
12.3%
e 5160
 
8.5%
t 4680
 
7.7%
a 4440
 
7.3%
s 4440
 
7.3%
o 4320
 
7.1%
r 4080
 
6.7%
n 2880
 
4.8%
c 2400
 
4.0%
l 2160
 
3.6%
Other values (30) 18480
30.6%
Common
ValueCountFrequency (%)
3360
82.4%
) 360
 
8.8%
( 360
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 7440
 
11.5%
e 5160
 
8.0%
t 4680
 
7.2%
a 4440
 
6.9%
s 4440
 
6.9%
o 4320
 
6.7%
r 4080
 
6.3%
3360
 
5.2%
n 2880
 
4.5%
c 2400
 
3.7%
Other values (33) 21360
33.1%

Unnamed: 133
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4920
Missing (%)100.0%
Memory size38.6 KiB

Correlations

2024-01-22T12:01:14.311493image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
abdominal_painabnormal_menstruationacidityacute_liver_failurealtered_sensoriumanxietyback_painbelly_painblackheadsbladder_discomfortblisterblood_in_sputumbloody_stoolblurred_and_distorted_visionbreathlessnessbrittle_nailsbruisingburning_micturitionchest_painchillscold_hands_and_feetscomacongestionconstipationcontinuous_feel_of_urinecontinuous_sneezingcoughcrampsdark_urinedehydrationdepressiondiarrhoeadischromic _patchesdistention_of_abdomendizzinessdrying_and_tingling_lipsenlarged_thyroidexcessive_hungerextra_marital_contactsfamily_historyfast_heart_ratefatiguefluid_overload.1foul_smell_of urineheadachehigh_feverhip_joint_painhistory_of_alcohol_consumptionincreased_appetiteindigestioninflammatory_nailsinternal_itchingirregular_sugar_levelirritabilityirritation_in_anusitchingjoint_painknee_painlack_of_concentrationlethargyloss_of_appetiteloss_of_balanceloss_of_smellmalaisemild_fevermood_swingsmovement_stiffnessmucoid_sputummuscle_painmuscle_wastingmuscle_weaknessnauseaneck_painnodal_skin_eruptionsobesitypain_behind_the_eyespain_during_bowel_movementspain_in_anal_regionpainful_walkingpalpitationspassage_of_gasespatches_in_throatphlegmpolyuriaprognosisprominent_veins_on_calfpuffy_face_and_eyespus_filled_pimplesreceiving_blood_transfusionreceiving_unsterile_injectionsred_sore_around_nosered_spots_over_bodyredness_of_eyesrestlessnessrunny_noserusty_sputumscurringshiveringsilver_like_dustingsinus_pressureskin_peelingskin_rashslurred_speechsmall_dents_in_nailsspinning_movementsspotting_ urinationstiff_neckstomach_bleedingstomach_painsunken_eyessweatingswelled_lymph_nodesswelling_jointsswelling_of_stomachswollen_blood_vesselsswollen_extremetiesswollen_legsthroat_irritationtoxic_look_(typhos)ulcers_on_tongueunsteadinessvisual_disturbancesvomitingwatering_from_eyesweakness_in_limbsweakness_of_one_body_sideweight_gainweight_lossyellow_crust_oozeyellow_urineyellowing_of_eyesyellowish_skin
abdominal_pain1.0000.1150.1100.2970.0760.0760.1110.2770.0740.0760.0760.0790.0760.1390.1620.0790.0760.1080.2080.0700.0760.3050.0790.1410.0760.1100.1840.0760.6640.0740.1130.1520.0740.2770.1380.0760.0790.1640.0740.1110.1130.1490.2770.0720.1530.0540.0760.2770.0790.1310.0760.2770.0760.1670.0760.2620.2680.0760.0760.0150.4850.1390.0790.0450.0740.1110.0760.0760.0190.0740.1130.3600.1110.0740.1110.0790.0760.0760.1110.0790.2770.0740.1420.0790.9680.0760.0760.0740.2860.2860.0760.1130.0790.1110.0790.0790.0740.0740.0760.0790.0760.2240.0790.0760.0740.0740.1110.3050.1100.0740.2050.1400.1110.2770.0740.0790.0760.0790.2770.0740.0760.0760.4790.0740.0740.0740.0760.0150.0760.2770.5260.732
abnormal_menstruation0.1151.0000.0450.0280.0280.0280.0450.0280.0270.0280.0280.0290.0280.0580.0690.6950.0280.0440.0890.0970.6770.0290.0290.0450.0280.0450.0790.0280.0790.0270.4790.2540.0270.0280.3630.0280.6950.2940.0270.0450.4520.2450.0280.0260.1220.1380.0280.0280.0290.0450.0280.0280.0280.6920.0280.0880.0890.0280.0280.2970.1230.0580.0290.0900.0600.9710.0280.0280.0710.0270.4790.1230.0450.0270.0450.0290.0280.0280.0450.0290.0280.0270.0600.0290.9960.0280.6770.0270.0290.0290.0280.0460.0290.4590.0290.0290.0270.0270.0280.0290.0280.0960.0290.0280.0270.0270.0450.0290.0450.0270.2200.0590.0450.0280.0270.6950.0280.0290.0280.0270.0280.0280.1790.0270.0270.0270.6770.2970.0280.0280.0990.106
acidity0.1100.0451.0000.0270.0270.0270.0430.0270.0260.0270.0270.0280.0270.3540.0660.0280.0270.0420.1960.0930.0270.0280.0280.0430.0270.0430.2330.0270.0760.0260.4460.0750.0260.0270.0550.0270.0280.2910.0260.0430.0440.1730.0270.0240.1300.1330.0270.0270.0280.4600.0270.0270.0270.2850.0270.0840.0850.0270.0270.0660.1180.0560.0280.0860.0570.0430.0270.0270.0680.0260.0440.1180.0430.0260.0430.0280.0270.0270.0430.0280.0270.0260.0570.0280.9560.0270.0270.0260.0280.0280.0270.0440.0280.0430.0280.0280.0260.0260.0270.0280.0270.0920.0280.0270.0260.0260.4530.0280.4310.0260.0840.0560.0430.0270.0260.0280.0270.0280.0270.6060.0270.6660.0120.0260.0260.0260.0270.0660.0270.0270.0950.101
acute_liver_failure0.2970.0280.0271.0000.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.9700.0140.0270.0130.0270.0510.0130.3980.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1730.0130.0100.0810.2290.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.3580.0130.0130.0450.2770.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.2580.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.9700.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.3430.300
altered_sensorium0.0760.0280.0270.0131.0000.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.2410.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1580.0120.0120.9130.0130.0450.0130.0130.0650.070
anxiety0.0760.0280.0270.0130.0131.0000.0270.0130.0120.0130.0130.0140.0130.5290.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.9420.0140.4760.0120.0270.0280.1730.0130.0100.2600.0930.0130.0130.0140.0270.0130.0130.0130.4690.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.2580.0270.0120.0270.0140.0130.0130.0270.9700.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.9700.0130.0120.0120.0270.0140.0270.0120.3600.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.070
back_pain0.1110.0450.0430.0270.0270.0271.0000.0270.0260.0270.0270.0280.0270.0570.0670.0280.0270.0430.0870.2000.0270.0280.0280.0440.0270.0430.0760.0270.0770.0260.0450.0760.0260.0270.3290.0270.0280.0680.0260.0440.0450.0450.0270.0250.1530.1080.0270.0270.0280.0430.0270.0270.0270.0690.0270.0860.2280.0270.0270.0670.1500.3250.0280.2230.0580.0440.0270.0270.3000.0260.0450.1510.4180.0260.0440.7140.0270.0270.0440.0280.0270.0260.0580.0280.9710.0270.0270.0260.0280.0280.0270.4660.0280.0440.0280.0280.0260.0260.0270.0280.0270.2030.0280.0270.0260.0260.0440.0280.0430.0260.0860.0570.0440.0270.0260.0280.0270.0280.0270.0260.0270.0270.0470.0260.5970.0260.0270.0670.0270.0270.0960.103
belly_pain0.2770.0280.0270.0130.0130.0130.0271.0000.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.3480.0130.0140.0140.6570.0130.0270.0510.0130.0520.0120.0280.4000.0120.0130.0360.0130.0140.0450.0120.0270.0280.1900.0130.0100.2600.2470.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.2580.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.9420.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.070
blackheads0.0740.0270.0260.0120.0120.0120.0260.0121.0000.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.8820.0130.0130.0120.0270.0130.0260.0130.0130.8820.0110.0120.0130.0120.3190.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
bladder_discomfort0.0760.0280.0270.0130.0130.0130.0270.0130.0121.0000.0130.0140.0130.0370.0440.0140.0130.6360.0590.0640.0130.0140.0140.0270.9420.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.8830.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
blister0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0131.0000.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.1930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.9420.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.3290.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.9420.0130.0650.070
blood_in_sputum0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0141.0000.0140.0380.4680.0150.0140.0270.3870.3360.0140.0150.0150.0280.0140.0280.4120.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.0840.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.0600.0140.0140.0460.2840.0380.0150.3850.5650.0280.0140.0140.0470.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.5650.0150.9960.0140.0140.0130.0150.0150.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.3700.5700.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1800.0130.0130.0130.0140.4650.0140.0140.3530.072
bloody_stool0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0141.0000.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.6570.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.9420.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.9420.9420.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
blurred_and_distorted_vision0.1390.0580.3540.0370.0370.5290.0570.0370.0350.0370.0370.0380.0371.0000.0840.0380.0370.0550.1090.1180.0370.0380.0380.0570.0370.0560.0960.0370.0970.0350.3420.0960.0350.0370.0710.5290.0380.8150.0350.0570.0570.1320.0370.0340.2590.1680.0370.0370.5450.3540.0370.0370.5290.5110.0370.1070.1080.0370.0370.2080.1500.0720.0380.1090.0730.0570.0370.0370.0870.0350.0570.0510.0570.0350.3480.0380.0370.0370.0570.5450.0370.0350.0730.5450.9690.0370.0370.0350.0380.0380.0370.0570.0380.3480.0380.0380.0350.0350.0370.0380.0370.1170.5450.0370.0350.0350.3480.0380.0560.0350.1390.0720.0570.0370.0350.0380.0370.0380.0370.0350.0370.5290.0380.0350.0350.0350.0370.2080.0370.0370.1200.129
breathlessness0.1620.0690.0660.0440.0440.0440.0670.0440.0430.0440.0440.4680.0440.0841.0000.0460.0440.0650.5380.2720.0440.0460.0460.0670.0440.0660.5880.0440.1130.0430.0680.1120.0430.0440.0830.0440.0460.1000.0430.2900.3050.2030.0440.0410.1720.3130.0440.0440.0460.0660.0440.0440.0440.1010.0440.1250.1260.0440.0440.0990.0000.0840.0460.3170.2210.0670.0440.4550.1010.0430.0680.1730.0670.0430.0670.0460.0440.0440.0670.0460.0440.0430.5160.0460.9610.0440.0440.0430.0460.0460.0440.0680.0460.0670.0460.4680.0430.0430.0440.0460.0440.1370.0460.0440.0430.0430.0670.0460.0660.0430.5100.2240.0670.0440.0430.0460.0440.0460.0440.0430.0440.0440.0390.0430.0430.0430.0440.1590.0440.0440.0720.150
brittle_nails0.0790.6950.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0461.0000.0140.0270.0610.0660.9700.0150.0150.0280.0140.0280.0530.0140.0530.0130.7040.0530.0130.0140.5500.0140.9960.0470.0130.0280.0290.1620.0140.0120.0840.0950.0140.0140.0150.0280.0140.0140.0140.4820.0140.0600.0600.0140.0140.4650.0850.0380.0150.0610.0390.6760.0140.0140.0470.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.0390.0150.9960.0140.9700.0130.0150.0150.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.0390.0280.0140.0130.9960.0140.0150.0140.0130.0140.0140.1240.0130.0130.0130.9700.0460.0140.0140.0670.072
bruising0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0141.0000.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.9420.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1730.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.6570.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.9420.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.9130.0140.9420.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
burning_micturition0.1080.0440.0420.0260.0260.0260.0430.0260.0250.6360.0260.0270.0260.0550.0650.0270.0261.0000.0840.0920.0260.0270.0270.0430.6360.0420.0740.0260.0750.0250.0430.0740.0250.0260.0540.0260.0270.0660.0250.0430.0430.1710.0260.5920.1150.1310.0260.0260.0270.0420.0260.0260.0260.0670.0260.2060.0830.0260.0260.0650.1160.0550.0270.0850.0560.0430.0260.0260.0670.0250.0430.1160.0430.0250.0430.0270.0260.0260.0430.0270.0260.0250.0560.0270.9420.0260.0260.0250.0270.0270.0260.0430.0270.0430.0270.0270.0250.0250.0260.0270.0260.1650.0270.0260.0250.6140.0430.0270.4100.0250.0830.0550.0430.0260.0250.0270.0260.0270.0260.0250.0260.0260.1690.0250.0250.0250.0260.0650.0260.0260.0930.100
chest_pain0.2080.0890.1960.0590.0590.0590.0870.0590.0570.0590.0590.3870.0590.1090.5380.0610.0590.0841.0000.3610.0590.0610.3870.0870.0590.2300.6770.0590.1450.0570.0880.1440.0570.0590.1100.0590.0610.1290.0570.0870.2360.0800.0590.0550.0660.1930.0590.0590.0610.0860.0590.0590.0590.1310.0590.1610.1620.0590.3310.1280.0570.1210.3870.4140.1560.0870.0590.0590.1030.0570.0880.2230.0870.0570.0870.0610.0590.0590.0870.0610.0590.0570.6850.0610.9770.0590.0590.0570.0610.0610.0590.0880.3870.0870.3870.3870.0570.0570.0590.3870.0590.1760.0610.0590.0570.0570.0870.0610.2130.0570.3950.4190.0870.0590.0570.0610.0590.3870.0590.3430.0590.0590.0540.0570.0570.0570.0590.0980.0590.0590.0000.192
chills0.0700.0970.0930.0640.0640.0640.2000.3480.0620.0640.0640.3360.0640.1180.2720.0660.0640.0920.3611.0000.0640.0660.3360.2000.0640.4450.4010.0640.1580.0620.0960.2140.0620.0640.1170.0640.0660.1400.0620.0950.1950.2690.0640.0600.3400.5400.0640.0640.0660.0930.0640.0640.0640.1420.0640.1750.0000.0640.0640.1390.0510.1180.3360.5100.1190.0950.0640.0640.4830.0620.0960.1950.0950.0620.0950.3360.0640.0640.0950.0660.0640.0620.5930.0660.9660.0640.0640.0620.0660.0660.0640.1800.3360.0950.3360.3360.0620.2930.0640.3360.0640.0250.0660.0640.0620.0620.0950.0660.0930.0620.3410.3550.0950.0640.0620.0660.0640.3360.3480.0620.0640.0640.1430.2930.0620.0620.0640.0620.0640.0640.0220.209
cold_hands_and_feets0.0760.6770.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.9700.0130.0260.0590.0641.0000.0140.0140.0270.0130.0270.0510.0130.0520.0120.6860.0510.0120.0130.5340.0130.9700.0450.0120.0270.0280.1560.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.4690.0130.0580.0580.0130.0130.4510.0820.0370.0140.0590.0380.6570.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.9420.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.9700.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.9420.0450.0130.0130.0650.070
coma0.3050.0290.0280.9700.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.0610.0660.0141.0000.0150.0280.0140.0280.0530.0140.4100.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.0840.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.3680.0140.0140.0460.2840.0380.0150.0610.0390.0280.0140.0140.0470.0130.0290.2660.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.0390.0150.9960.0140.0140.0130.0150.0150.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.9960.0280.0130.0600.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1800.0130.0130.0130.0140.0460.0140.0140.3530.309
congestion0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.3870.3360.0140.0151.0000.0280.0140.6860.4120.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.2680.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.0600.0140.0140.0460.0850.0380.9960.3630.0390.0280.0140.0140.4820.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.5650.0150.9960.0140.0140.0130.0150.0150.0140.0290.9960.0280.9960.0150.0130.0130.0140.9960.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.5400.0280.0140.0130.0150.0140.9960.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.0140.0670.072
constipation0.1410.0450.0430.0270.0270.0270.0440.6570.0260.0270.0270.0280.6570.0570.0670.0280.0270.0430.0870.2000.0270.0280.0281.0000.0270.0430.0760.0270.0770.0260.0450.2470.0260.0270.0560.0270.0280.0680.0260.0440.0450.0450.0270.0250.1250.1080.0270.0270.0280.0430.0270.0270.0270.0690.6570.0860.0860.0270.0270.0670.1200.0570.0280.0870.0580.0440.0270.0270.0690.0260.0450.1240.0440.0260.0440.0280.6570.6570.0440.0280.0270.0260.0580.0280.9690.0270.0270.0260.0280.0280.0270.0450.0280.0440.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0260.0440.0280.0430.0260.0860.0570.0440.0270.0260.0280.0270.0280.6570.0260.0270.0270.0340.0260.0260.0260.0270.0670.0270.0270.0960.103
continuous_feel_of_urine0.0760.0280.0270.0130.0130.0130.0270.0130.0120.9420.0130.0140.0130.0370.0440.0140.0130.6360.0590.0640.0130.0140.0140.0271.0000.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.8830.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
continuous_sneezing0.1100.0450.0430.0270.0270.0270.0430.0270.0260.0270.0270.0280.0270.0560.0660.0280.0270.0420.2300.4450.0270.0280.6860.0430.0271.0000.2520.0270.0760.0260.0440.0750.0260.0270.0550.0270.0280.0670.0260.0430.0440.0380.0270.0240.1300.1000.0270.0270.0280.0430.0270.0270.0270.0680.0270.0840.0850.0270.0270.0660.1180.0560.6860.2120.0570.0430.0270.0270.3050.0260.0440.1180.0430.0260.0430.0280.0270.0270.0430.0280.0270.0260.3690.0280.9560.0270.0270.0260.0280.0280.0270.0440.6860.0430.6860.0280.0260.6060.0270.6860.0270.0920.0280.0270.0260.0260.0430.0280.0430.0260.0840.3500.0430.0270.0260.0280.0270.6860.0270.0260.0270.0270.1720.6060.0260.0260.0270.0660.0270.0270.0950.101
cough0.1840.0790.2330.0510.0510.0510.0760.0510.0500.0510.0510.4120.0510.0960.5880.0530.0510.0740.6770.4010.0510.0530.4120.0760.0510.2521.0000.0510.1280.0500.0780.1280.0500.0510.0950.0510.0530.1140.0500.2280.2590.2580.0510.0480.0290.3840.0510.0510.0530.0750.0510.0510.0510.1160.0510.1420.1430.0510.0510.1130.0220.0960.4120.4540.1790.0760.0510.3750.1270.0500.0780.1970.0760.0500.0760.0530.0510.0510.0760.0530.0510.0500.7280.0530.9620.0510.0510.0500.0530.0530.0510.0780.4120.0760.4120.4120.0500.0500.0510.4120.0510.1550.0530.0510.0500.0500.0760.0530.2520.0500.2550.4520.0760.0510.0500.0530.0510.4120.0510.3880.0510.0510.0000.0500.0500.0500.0510.1210.0510.0510.0310.170
cramps0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.9420.0260.0590.0640.0130.0140.0140.0270.0130.0270.0511.0000.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1730.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.6570.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.9420.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.9130.0140.9420.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
dark_urine0.6640.0790.0760.3980.0520.0520.0770.0520.0500.0520.0520.0530.0520.0970.1130.0530.0520.0750.1450.1580.0520.4100.0530.0770.0520.0760.1280.0521.0000.0500.0780.0830.0500.0520.0960.0520.0530.1150.0500.0770.0780.2700.0520.0480.1970.0810.0520.0520.0530.0760.0520.0520.0520.1160.0520.2520.4480.0520.0520.1190.4560.0970.0530.0570.1780.0770.0520.0520.1250.0500.0780.2860.0770.0500.0770.0530.0520.0520.0770.0530.0520.0500.0990.0530.9670.0520.0520.0500.4100.4100.0520.0780.0530.0770.0530.0530.0500.0500.0520.0530.0520.1560.0530.0520.0500.0500.0770.4100.0760.0500.1430.0980.0770.0520.0500.0530.0520.0530.0520.0500.0520.0520.2730.0500.0500.0500.0520.1190.0520.3980.6060.709
dehydration0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0501.0000.0270.3880.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.8820.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1520.0110.0110.0110.0120.0430.0120.0120.0630.068
depression0.1130.4790.4460.0280.0280.0280.0450.0280.0270.0280.0280.0290.0280.3420.0680.7040.0280.0430.0880.0960.6860.0290.0290.0450.0280.0440.0780.0280.0780.0271.0000.0780.0270.0280.3690.0280.7040.2800.0270.0450.0460.0270.0280.0250.1210.1360.0280.0280.0290.4460.0280.0280.0280.6630.0280.0870.0870.0280.0280.3020.1220.0570.0290.0890.0590.4660.0280.0280.0700.0270.0460.1210.0450.0270.0450.0290.0280.0280.0450.0290.0280.0270.0590.0290.9830.0280.6860.0270.0290.0290.0280.0460.0290.0450.0290.0290.0270.0270.0280.0290.0280.0950.0290.0280.0270.0270.4390.0290.0440.0270.0870.0580.0450.0280.0270.7040.0280.0290.0280.0270.0280.6480.1770.0270.0270.0270.6860.0680.0280.0280.0970.104
diarrhoea0.1520.2540.0750.0510.0510.0510.0760.4000.0500.0510.0510.0530.0510.0960.1120.0530.0510.0740.1440.2140.0510.0530.0530.2470.0510.0750.1280.0510.0830.3880.0781.0000.0500.0510.0950.0510.0530.1180.0500.0760.2410.0000.0510.0480.1200.0830.0510.0510.0530.0750.0510.0510.0510.1270.0510.1420.0520.0510.0510.1130.0330.0960.0530.1450.1790.2470.0510.0510.3610.0500.2590.2810.0760.0500.0760.0530.0510.0510.0760.0530.0510.0500.0980.0530.9620.0510.0510.0500.0530.0530.0510.0780.0530.2470.0530.0530.0500.0500.0510.0530.0510.1550.0530.0510.0500.0500.0760.0530.0750.3880.2440.0970.0760.0510.0500.0530.0510.0530.4000.0500.0510.0510.2610.0500.0500.0500.0510.1210.0510.0510.0310.000
dischromic _patches0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0501.0000.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.3240.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.8820.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.2960.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
distention_of_abdomen0.2770.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0121.0000.0360.0130.0140.0450.0120.0270.0280.1220.9420.0100.0810.0930.0130.9420.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.9420.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.300
dizziness0.1380.3630.0550.0360.0360.0360.3290.0360.0350.0360.0360.0380.0360.0710.0830.5500.0360.0540.1100.1170.5340.0380.0380.0560.0360.0550.0950.0360.0960.0350.3690.0950.0350.0361.0000.0360.5500.0850.0350.0560.0570.0460.0360.0340.0310.1660.0360.0360.0380.0550.0360.0360.0360.2210.0360.1060.1070.0360.5020.2120.1480.5900.0380.1080.0720.3520.0360.0360.0860.0350.0570.1480.3520.0350.0560.0380.0360.0360.0560.0380.0360.0350.0720.0380.9600.0360.5340.0350.0380.0380.0360.0570.0380.0560.0380.0380.0350.0350.0360.0380.0360.1160.0380.0360.0350.0350.0560.0380.0550.0350.1060.0720.0560.0360.0350.5500.0360.0380.0360.0350.0360.0360.2150.0350.5170.0350.5340.0840.0360.0360.1190.127
drying_and_tingling_lips0.0760.0280.0270.0130.0130.9420.0270.0130.0120.0130.0130.0140.0130.5290.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0361.0000.0140.4760.0120.0270.0280.1730.0130.0100.2600.0930.0130.0130.0140.0270.0130.0130.0130.4690.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.2580.0270.0120.0270.0140.0130.0130.0270.9700.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.9700.0130.0120.0120.0270.0140.0270.0120.3600.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.070
enlarged_thyroid0.0790.6950.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.9960.0140.0270.0610.0660.9700.0150.0150.0280.0140.0280.0530.0140.0530.0130.7040.0530.0130.0140.5500.0141.0000.0470.0130.0280.0290.1620.0140.0120.0840.0950.0140.0140.0150.0280.0140.0140.0140.4820.0140.0600.0600.0140.0140.4650.0850.0380.0150.0610.0390.6760.0140.0140.0470.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.0390.0150.9960.0140.9700.0130.0150.0150.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.0390.0280.0140.0130.9960.0140.0150.0140.0130.0140.0140.1240.0130.0130.0130.9700.0460.0140.0140.0670.072
excessive_hunger0.1640.2940.2910.0450.0450.4760.0680.0450.0440.0450.0450.0470.0450.8150.1000.0470.0450.0660.1290.1400.0450.0470.0470.0680.0450.0670.1140.0450.1150.0440.2800.1180.0440.0450.0850.4760.0471.0000.0440.0680.2800.2110.0450.0420.1900.1980.0450.0450.4620.2910.0450.0450.4480.7010.0450.1270.1280.0450.0450.1550.1770.0850.0470.1300.0870.2850.0450.0450.1030.0440.2990.0000.0680.0440.2850.0470.0450.0450.0680.4890.0450.0440.0870.4620.9750.0450.0450.0440.0470.0470.0450.0690.0470.6430.0470.0470.0440.0440.0450.0470.0450.1390.4890.0450.0440.0440.2850.0470.0670.0440.3190.0860.0680.0450.0440.0470.0450.0470.0450.0440.0450.4480.0920.0440.0440.0440.0450.4150.0450.0450.1420.152
extra_marital_contacts0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0441.0000.0260.0270.1180.0120.0090.0790.2220.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.8820.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.8820.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
family_history0.1110.0450.0430.0270.0270.0270.0440.0270.0260.0270.0270.0280.0270.0570.2900.0280.0270.0430.0870.0950.0270.0280.0280.0440.0270.0430.2280.0270.0770.0260.0450.0760.0260.0270.0560.0270.0280.0680.0261.0000.0450.2370.0270.0250.1190.0950.0270.0270.0280.0430.0270.0270.0270.0690.0270.0860.0860.0270.0270.0670.1230.0570.0280.0870.0580.0440.0270.6570.0690.0260.0450.1240.0440.0260.0440.0280.0270.0270.0440.0280.0270.0260.0580.0280.9690.0270.0270.0260.0280.0280.0270.0450.0280.0440.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0260.0440.0280.0430.0260.0860.0570.0440.0270.0260.0280.0270.0280.0270.0260.0270.0270.1740.0260.0260.0260.0270.0670.0270.0270.1650.162
fast_heart_rate0.1130.4520.0440.0280.0280.0280.0450.0280.0270.0280.0280.0290.0280.0570.3050.0290.0280.0430.2360.1950.0280.0290.0290.0450.0280.0440.2590.0280.0780.0270.0460.2410.0270.0280.0570.0280.0290.2800.0270.0451.0000.2530.0280.0250.1200.1030.0280.0280.0290.0440.0280.0280.0280.2940.0280.0870.0870.0280.0280.0680.1220.0570.0290.2180.0590.4390.0280.0280.0700.0270.4590.1210.0450.0270.0450.0290.0280.0280.0450.0290.0280.0270.3570.0290.9830.0280.0280.0270.0290.0290.0280.0460.0290.4390.0290.7040.0270.0270.0280.0290.0280.0950.0290.0280.0270.0270.0450.0290.0440.0270.5240.0580.0450.0280.0270.0290.0280.0290.0280.0270.0280.0280.1770.0270.0270.0270.0280.2820.0280.0280.0970.104
fatigue0.1490.2450.1730.1730.1220.1730.0450.1900.1180.1220.1220.1790.1220.1320.2030.1620.1730.1710.0800.2690.1560.1790.1790.0450.1220.0380.2580.1730.2700.1180.0270.0000.1180.1220.0460.1730.1620.2110.1180.2370.2531.0000.1220.1150.1040.4120.1220.1220.1790.1730.1220.1220.1730.2100.1220.0680.0640.1220.1220.3530.3150.2190.1790.4640.1320.2370.1220.1560.0480.1180.0400.2060.1760.1180.2490.1790.1220.1220.1760.1790.1220.1180.3160.1790.9520.1730.1560.1180.1790.1790.1220.2530.1790.2490.1790.1790.1180.1180.1220.1790.1220.1040.1790.1220.1180.1180.1760.1790.1730.1180.1990.3130.1760.1220.1670.1620.1730.1790.1900.1180.1220.1220.0000.1180.1180.1180.1560.3620.1220.1730.2580.194
fluid_overload.10.2770.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.9420.0360.0130.0140.0450.0120.0270.0280.1221.0000.0100.0810.0930.0130.9420.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.9420.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.300
foul_smell_of urine0.0720.0260.0240.0100.0100.0100.0250.0100.0090.8830.0100.0120.0100.0340.0410.0120.0100.5920.0550.0600.0100.0120.0120.0250.8830.0240.0480.0100.0480.0090.0250.0480.0090.0100.0340.0100.0120.0420.0090.0250.0250.1150.0101.0000.0770.0870.0100.0100.0120.0240.0100.0100.0100.0430.0100.0540.0550.0100.0100.0420.0770.0340.0120.0560.0350.0250.0100.0100.0430.0090.0250.0770.0250.0090.0250.0120.0100.0100.0250.0120.0100.0090.0350.0120.9160.0100.0100.0090.0120.0120.0100.0250.0120.0250.0120.0120.0090.0090.0100.0120.0100.0600.0120.0100.0090.0090.0250.0120.0240.0090.0540.0350.0250.0100.0090.0120.0100.0120.0100.0090.0100.0100.1140.0090.0090.0090.0100.0420.0100.0100.0610.066
headache0.1530.1220.1300.0810.2410.2600.1530.2600.0790.0810.0810.0840.0810.2590.1720.0840.0810.1150.0660.3400.0810.0840.2680.1250.0810.1300.0290.0810.1970.0790.1210.1200.0790.0810.0310.2600.0840.1900.0790.1190.1200.1040.0810.0771.0000.2560.0810.0810.0840.1300.0810.0810.0810.1830.0810.0650.0580.0810.2410.0000.0400.2480.2680.2390.0460.1190.0810.0810.3800.0790.1200.3280.1190.0790.1190.2870.0810.0810.1190.2680.0810.0790.0580.0840.9600.0810.0810.0790.0840.0840.0810.3930.2680.1190.2680.0840.0790.0790.0810.2680.0810.0510.2680.0810.2520.0790.1250.0840.1170.0790.0820.2540.1190.0810.0790.0840.0810.2680.2600.0790.2600.2600.1980.0790.0790.2320.0810.1740.0810.0810.2430.260
high_fever0.0540.1380.1330.2290.0930.0930.1080.2470.0900.0930.1930.2360.0930.1680.3130.0950.0930.1310.1930.5400.0930.2360.2360.1080.0930.1000.3840.0930.0810.0900.1360.0830.0900.0930.1660.0930.0950.1980.2220.0950.1030.4120.0930.0870.2561.0000.0930.0930.0950.1330.0930.0930.0930.2010.0930.0340.0310.0930.0930.0240.1390.1680.2360.4640.2170.1350.0930.2290.3140.2220.1360.1350.1350.0900.1350.2360.0930.0930.1350.0950.0930.2220.4170.0950.9580.0930.0930.0900.0950.0950.1930.3340.2360.1350.2360.2360.0900.0900.0930.2360.0930.1160.0950.0930.0900.0900.1350.2360.1330.0900.1780.4130.1350.0930.0900.0950.0930.2360.2470.0900.0930.0930.1140.0900.0900.0900.0930.1390.1930.0930.0000.040
hip_joint_pain0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0931.0000.0130.0140.0270.0130.0130.0130.0460.0130.0580.3580.9420.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.6570.0120.0270.0140.0130.0130.6570.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.6570.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
history_of_alcohol_consumption0.2770.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.9420.0360.0130.0140.0450.0120.0270.0280.1220.9420.0100.0810.0930.0131.0000.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.9420.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.300
increased_appetite0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.5450.0460.0150.0140.0270.0610.0660.0140.0150.0150.0280.0140.0280.0530.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.4620.0130.0280.0290.1790.0140.0120.0840.0950.0140.0141.0000.0280.0140.0140.9700.0470.0140.0600.0600.0140.0140.4650.0850.0380.0150.0610.0390.0280.0140.0140.0470.0130.0290.0840.0280.0130.6760.0150.0140.0140.0280.0150.0140.0130.0390.9960.9960.0140.0140.0130.0150.0150.0140.0290.0150.6760.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1240.0130.0130.0130.0140.4650.0140.0140.0670.072
indigestion0.1310.0450.4600.0270.0270.0270.0430.0270.0260.0270.0270.0280.0270.3540.0660.0280.0270.0420.0860.0930.0270.0280.0280.0430.0270.0430.0750.0270.0760.0260.4460.0750.0260.0270.0550.0270.0280.2910.0260.0430.0440.1730.0270.0240.1300.1330.0270.0270.0281.0000.0270.6270.0270.2850.0270.0840.0850.0270.0270.0660.1000.0560.0280.0860.0570.0430.0270.0270.0680.0260.0440.1180.0430.0260.0430.0280.0270.0270.0430.0280.6270.0260.0570.0280.9560.0270.0270.0260.0280.0280.0270.0440.0280.0430.0280.0280.0260.0260.0270.0280.0270.0920.0280.0270.0260.0260.4530.0280.0430.0260.0840.0560.0430.0270.0260.0280.0270.0280.0270.0260.0270.6660.0270.0260.0260.0260.0270.0660.0270.0270.0950.101
inflammatory_nails0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0271.0000.0130.0130.0460.0130.0580.3580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.9420.0140.9420.3290.0140.9420.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
internal_itching0.2770.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.6270.0131.0000.0130.0460.0130.0580.0580.0130.0130.0450.2380.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.9420.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.070
irregular_sugar_level0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.5290.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.4480.0120.0270.0280.1730.0130.0100.0810.0930.0130.0130.9700.0270.0130.0131.0000.0460.0130.0580.0580.0130.0130.4510.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.6570.0140.0130.0130.0270.0140.0130.0120.0380.9700.9700.0130.0130.0120.0140.0140.0130.0280.0140.6570.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.4510.0130.0130.0650.070
irritability0.1670.6920.2850.0460.0460.4690.0690.0460.0440.0460.0460.0470.0460.5110.1010.4820.0460.0670.1310.1420.4690.0470.0470.0690.0460.0680.1160.0460.1160.0440.6630.1270.0440.0460.2210.4690.4820.7010.0440.0690.2940.2100.0460.0430.1830.2010.0460.0460.0470.2850.0460.0460.0461.0000.0460.1290.1290.0460.0460.1650.1790.0870.0470.1310.0880.6730.0460.0460.1040.0440.3140.0000.0690.0440.0690.0470.0460.0460.0690.4820.0460.0440.0880.0470.9890.0460.4690.0440.0470.0470.0460.0700.0470.3000.0470.0470.0440.0440.0460.0470.0460.1410.4820.0460.0440.0440.2800.0470.0680.0440.3240.0880.0690.0460.0440.4820.0460.0470.0460.0440.0460.4420.0980.0440.0440.0440.4690.1650.0460.0460.1440.154
irritation_in_anus0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.9420.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.6570.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0461.0000.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.9420.9420.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
itching0.2620.0880.0840.0580.0580.0580.0860.0580.0560.0580.0580.0600.0580.1070.1250.0600.0580.2060.1610.1750.0580.0600.0600.0860.0580.0840.1420.0580.2520.0560.0870.1420.3240.0580.1060.0580.0600.1270.0560.0860.0870.0680.0580.0540.0650.0340.0580.0580.0600.0840.0580.0580.0580.1290.0581.0000.1590.0580.0580.3100.2290.1070.0600.2200.1330.0860.0580.0580.1290.0560.0870.0670.0860.3240.0860.0600.0580.0580.0860.0600.0580.0560.1090.0600.9620.0580.0580.0560.3700.3700.0580.2250.0600.0860.0600.0600.0560.0560.0580.0600.0580.3170.0600.0580.0560.3480.0860.0600.2010.0560.1580.1360.0860.0580.0560.0600.0580.0600.0580.0560.0580.0580.0550.0560.0560.0560.0580.0900.0580.3600.1720.300
joint_pain0.2680.0890.0850.3580.0580.0580.2280.0580.0560.0580.0580.0600.0580.1080.1260.0600.0580.0830.1620.0000.0580.3680.0600.0860.0580.0850.1430.0580.4480.0560.0870.0520.0560.0580.1070.0580.0600.1280.0560.0860.0870.0640.0580.0550.0580.0310.3580.0580.0600.0850.3580.0580.0580.1290.0580.1591.0000.3580.0580.1270.3930.1080.0600.0090.1450.0860.0580.0580.3100.0560.0870.3860.2110.0560.0860.3680.0580.0580.2110.0600.0580.0560.1100.0600.9660.0580.0580.0560.0600.0600.0580.2060.0600.0860.0600.0600.0560.0560.3580.0600.3580.1700.0600.3580.0560.0560.0860.3680.0850.0560.1590.1090.2110.0580.0560.0600.0580.0600.0580.0560.0580.0580.1990.0560.0560.0560.0580.1270.0580.0580.3500.297
knee_pain0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.9420.0130.0140.0270.0130.0130.0130.0460.0130.0580.3581.0000.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.6570.0120.0270.0140.0130.0130.6570.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.6570.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
lack_of_concentration0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.3310.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.5020.0130.0140.0450.0120.0270.0280.1220.0130.0100.2410.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0131.0000.0450.0820.5290.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
lethargy0.0150.2970.0660.0450.0450.0450.0670.0450.0430.0450.0450.0460.0450.2080.0990.4650.0450.0650.1280.1390.4510.0460.0460.0670.0450.0660.1130.0450.1190.0430.3020.1130.0430.0450.2120.0450.4650.1550.0430.0670.0680.3530.0450.0420.0000.0240.0450.0450.4650.0660.0450.0450.4510.1650.0450.3100.1270.0450.0451.0000.1790.0850.0460.3250.2020.2880.0450.0450.1020.0430.0680.1750.0670.0430.2880.0460.0450.0450.0670.0460.0450.0430.0860.4650.9680.0450.4510.0430.4650.4650.0450.3020.0460.2880.0460.0460.0430.0430.0450.0460.0450.0650.0460.0450.0430.0430.0670.0460.0660.0430.1260.2050.0670.0450.0430.4650.0450.0460.0450.0430.0450.0450.2540.0430.0430.0430.4510.1570.0450.4510.0700.039
loss_of_appetite0.4850.1230.1180.2770.0820.0820.1500.0820.0800.0820.0820.2840.0820.1500.0000.0850.0820.1160.0570.0510.0820.2840.0850.1200.0820.1180.0220.0820.4560.0800.1220.0330.0800.0820.1480.0820.0850.1770.0800.1230.1220.3150.0820.0770.0400.1390.0820.0820.0850.1000.0820.2380.0820.1790.0820.2290.3930.0820.0820.1791.0000.1500.0850.4080.4800.1200.0820.0820.1890.0800.1220.4510.1200.0800.1200.2840.0820.0820.1200.0850.2380.0800.0670.0850.9700.0820.0820.0800.2650.2650.0820.3890.0850.1200.0850.0850.0800.0800.0820.0850.0820.0470.0850.0820.0800.0800.1200.2840.1180.0800.0600.2730.1200.0820.0800.0850.0820.0850.0820.0800.0820.0820.3140.0800.0800.0800.0820.0000.0820.2570.7670.543
loss_of_balance0.1390.0580.0560.0370.0370.0370.3250.0370.0350.0370.0370.0380.0370.0720.0840.0380.0370.0550.1210.1180.0370.0380.0380.0570.0370.0560.0960.0370.0970.0350.0570.0960.0350.0370.5900.0370.0380.0850.0350.0570.0570.2190.0370.0340.2480.1680.0370.0370.0380.0560.0370.0370.0370.0870.0370.1070.1080.0370.5290.0850.1501.0000.0380.1090.0730.0570.0370.0370.0870.0350.0570.0510.3480.0350.0570.0380.0370.0370.0570.0380.0370.0350.0730.0380.9690.0370.0370.0350.0380.0380.0370.0570.0380.0570.0380.0380.0350.0350.0370.0380.0370.1170.0380.0370.5130.0350.0570.0380.0560.0350.1070.0720.0570.0370.0350.0380.0370.0380.0370.0350.5290.0370.0380.0350.5130.0350.0370.0850.0370.0370.1200.129
loss_of_smell0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.3870.3360.0140.0150.9960.0280.0140.6860.4120.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.2680.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.0600.0140.0140.0460.0850.0381.0000.3630.0390.0280.0140.0140.4820.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.5650.0150.9960.0140.0140.0130.0150.0150.0140.0290.9960.0280.9960.0150.0130.0130.0140.9960.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.5400.0280.0140.0130.0150.0140.9960.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.0140.0670.072
malaise0.0450.0900.0860.0590.0590.0590.2230.0590.0570.0590.0590.3850.0590.1090.3170.0610.0590.0850.4140.5100.0590.0610.3630.0870.0590.2120.4540.0590.0570.0570.0890.1450.0570.0590.1080.0590.0610.1300.0570.0870.2180.4640.0590.0560.2390.4640.0590.0590.0610.0860.0590.0590.0590.1310.0590.2200.0090.0590.0590.3250.4080.1090.3631.0000.4110.0870.0590.0590.3030.0570.0890.0660.0870.0570.0870.3630.0590.0590.0870.0610.0590.0570.6540.0610.9820.0590.0590.0570.3850.3850.0590.5300.3630.0870.3630.3630.0570.0570.0590.3630.0590.1730.0610.0590.0570.0570.0870.0610.0860.0570.2100.6610.0870.0590.0570.0610.0590.3630.0590.0570.0590.0590.0590.0570.0570.0570.0590.0960.0590.3750.1920.019
mild_fever0.0740.0600.0570.0380.0380.0380.0580.0380.0360.0380.0380.5650.0380.0730.2210.0390.0380.0560.1560.1190.0380.0390.0390.0580.0380.0570.1790.0380.1780.0360.0590.1790.0360.0380.0720.0380.0390.0870.0360.0580.0590.1320.0380.0350.0460.2170.0380.0380.0390.0570.0380.0380.0380.0880.0380.1330.1450.0380.0380.2020.4800.0730.0390.4111.0000.0580.0380.0380.2270.0360.0590.0560.0580.0360.0580.0390.0380.0380.0580.0390.0380.0360.2860.0390.9870.0380.0380.0360.0390.0390.0380.3570.0390.0580.0390.0390.0360.0360.0380.0390.0380.1080.0390.0380.0360.0360.0580.0390.0570.0360.1470.6210.0580.0380.0360.0390.0380.0390.0380.0360.0380.0380.1440.0360.0360.0360.0380.2180.0380.0380.3820.096
mood_swings0.1110.9710.0430.0270.0270.0270.0440.0270.0260.0270.0270.0280.0270.0570.0670.6760.0270.0430.0870.0950.6570.0280.0280.0440.0270.0430.0760.0270.0770.0260.4660.2470.0260.0270.3520.0270.6760.2850.0260.0440.4390.2370.0270.0250.1190.1350.0270.0270.0280.0430.0270.0270.0270.6730.0270.0860.0860.0270.0270.2880.1200.0570.0280.0870.0581.0000.0270.0270.0690.0260.4660.1190.0440.0260.0440.0280.0270.0270.0440.0280.0270.0260.0580.0280.9690.0270.6570.0260.0280.0280.0270.0450.0280.4460.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0260.0440.0280.0430.0260.2130.0570.0440.0270.0260.6760.0270.0280.0270.0260.0270.0270.1740.0260.0260.0260.6570.2880.0270.0270.0960.103
movement_stiffness0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0271.0000.0130.0460.0120.6480.0820.0270.0120.0270.0140.0130.0130.6570.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.6570.0140.0270.0120.0580.0370.6570.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
mucoid_sputum0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.4550.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.3750.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.6570.0280.1560.0130.0100.0810.2290.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0131.0000.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
muscle_pain0.0190.0710.0680.0460.0460.0460.3000.0460.0440.0460.0460.0470.0460.0870.1010.0470.0460.0670.1030.4830.0460.0470.4820.0690.0460.3050.1270.0460.1250.0440.0700.3610.0440.0460.0860.0460.0470.1030.0440.0690.0700.0480.0460.0430.3800.3140.0460.0460.0470.0680.0460.0460.0460.1040.0460.1290.3100.0460.0460.1020.1890.0870.4820.3030.2270.0690.0460.0461.0000.0440.0700.3760.0690.0440.0690.4550.0460.0460.0690.0470.0460.0440.2270.0470.9890.0460.0460.0440.0470.0470.0460.2750.4820.0690.4820.0470.0440.0440.0460.4820.0460.0580.0470.0460.0440.0440.0690.0470.0680.0440.0950.2140.0690.0460.0440.0470.0460.4820.0460.0440.0460.0460.2130.0440.0440.0440.0460.1020.0460.0460.0740.043
muscle_wasting0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.8820.0260.0270.1180.0120.0090.0790.2220.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0441.0000.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.8820.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
muscle_weakness0.1130.4790.0440.0280.0280.0280.0450.0280.0270.0280.0280.0290.0280.0570.0680.0290.0280.0430.0880.0960.0280.0290.0290.0450.0280.0440.0780.0280.0780.0270.0460.2590.0270.0280.0570.0280.0290.2990.0270.0450.4590.0400.0280.0250.1200.1360.0280.0280.0290.0440.0280.0280.0280.3140.0280.0870.0870.0280.0280.0680.1220.0570.0290.0890.0590.4660.6480.0280.0700.0271.0000.1210.0450.0270.0450.0290.0280.0280.4390.0290.0280.0270.0590.0290.9830.0280.0280.0270.0290.0290.0280.0460.0290.4660.0290.0290.0270.0270.0280.0290.0280.0950.0290.0280.0270.0270.4390.0290.0440.0270.2250.0580.4390.0280.0270.0290.0280.0290.0280.0270.0280.0280.1770.0270.0270.0270.0280.3020.0280.0280.0970.104
nausea0.3600.1230.1180.2580.0820.2580.1510.2580.0800.0820.0820.0840.0820.0510.1730.0840.0820.1160.2230.1950.0820.2660.0840.1240.0820.1180.1970.0820.2860.0800.1210.2810.0800.0820.1480.2580.0840.0000.0800.1240.1210.2060.0820.0770.3280.1350.0820.0820.0840.1180.0820.0820.0820.0000.0820.0670.3860.0820.0820.1750.4510.0510.0840.0660.0560.1190.0820.0820.3760.0800.1211.0000.1190.0800.1190.2850.0820.0820.1190.2660.0820.0800.1520.0840.9660.0820.0820.0800.0840.0840.0820.1330.0840.1190.0840.0840.0800.0800.0820.0840.0820.0890.2660.0820.2500.0800.1190.2660.1180.0800.0790.1500.1190.0820.0800.0840.0820.0840.2580.0800.2580.0820.5240.0800.0800.0800.0820.1750.0820.0820.4590.405
neck_pain0.1110.0450.0430.0270.0270.0270.4180.0270.0260.0270.0270.0280.0270.0570.0670.0280.0270.0430.0870.0950.0270.0280.0280.0440.0270.0430.0760.0270.0770.0260.0450.0760.0260.0270.3520.0270.0280.0680.0260.0440.0450.1760.0270.0250.1190.1350.6570.0270.0280.0430.0270.0270.0270.0690.0270.0860.2110.6570.0270.0670.1200.3480.0280.0870.0580.0440.0270.0270.0690.0260.0450.1191.0000.0260.0440.0280.0270.0270.4460.0280.0270.0260.0580.0280.9690.0270.0270.0260.0280.0280.0270.0450.0280.0440.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0260.0440.0280.0430.0260.0860.0570.4460.0270.0260.0280.0270.0280.0270.0260.0270.0270.1740.0260.6370.0260.0270.0670.0270.0270.0960.103
nodal_skin_eruptions0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.8820.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.3240.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0261.0000.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.2960.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
obesity0.1110.0450.0430.0270.0270.0270.0440.0270.0260.0270.0270.0280.0270.3480.0670.0280.6570.0430.0870.0950.0270.0280.0280.0440.0270.0430.0760.6570.0770.0260.0450.0760.0260.0270.0560.0270.0280.2850.0260.0440.0450.2490.0270.0250.1190.1350.0270.0270.6760.0430.0270.0270.6570.0690.0270.0860.0860.0270.0270.2880.1200.0570.0280.0870.0580.0440.0270.0270.0690.0260.0450.1190.0440.0261.0000.0280.0270.0270.0440.0280.0270.0260.0580.6760.9690.6570.0270.0260.0280.0280.0270.0450.0280.4460.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0260.0440.0280.0430.0260.0860.0570.0440.0270.6370.0280.6570.0280.0270.0260.0270.0270.1740.0260.0260.0260.0270.2880.0270.0270.0960.103
pain_behind_the_eyes0.0790.0290.0280.0140.0140.0140.7140.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.0610.3360.0140.0150.0150.0280.0140.0280.0530.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.2870.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.3680.0140.0140.0460.2840.0380.0150.3630.0390.0280.0140.0140.4550.0130.0290.2850.0280.0130.0281.0000.0140.0140.0280.0150.0140.0130.0390.0150.9960.0140.0140.0130.0150.0150.0140.6670.0150.0280.0150.0150.0130.0130.0140.0150.0140.3390.0150.0140.0130.0130.0280.0150.0280.0130.0600.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1800.0130.0130.0130.0140.0460.0140.0140.0670.072
pain_during_bowel_movements0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.9420.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.6570.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.9420.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0141.0000.9420.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
pain_in_anal_region0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.9420.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.6570.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.9420.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.9421.0000.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
painful_walking0.1110.0450.0430.0270.0270.0270.0440.0270.0260.0270.0270.0280.0270.0570.0670.0280.0270.0430.0870.0950.0270.0280.0280.0440.0270.0430.0760.0270.0770.0260.0450.0760.0260.0270.0560.0270.0280.0680.0260.0440.0450.1760.0270.0250.1190.1350.6570.0270.0280.0430.0270.0270.0270.0690.0270.0860.2110.6570.0270.0670.1200.0570.0280.0870.0580.0440.6570.0270.0690.0260.4390.1190.4460.0260.0440.0280.0270.0271.0000.0280.0270.0260.0580.0280.9690.0270.0270.0260.0280.0280.0270.0450.0280.0440.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0260.4460.0280.0430.0260.0860.0570.9420.0270.0260.0280.0270.0280.0270.0260.0270.0270.1740.0260.0260.0260.0270.0670.0270.0270.0960.103
palpitations0.0790.0290.0280.0140.0140.9700.0280.0140.0130.0140.0140.0150.0140.5450.0460.0150.0140.0270.0610.0660.0140.0150.0150.0280.0140.0280.0530.0140.0530.0130.0290.0530.0130.0140.0380.9700.0150.4890.0130.0280.0290.1790.0140.0120.2680.0950.0140.0140.0150.0280.0140.0140.0140.4820.0140.0600.0600.0140.0140.0460.0850.0380.0150.0610.0390.0280.0140.0140.0470.0130.0290.2660.0280.0130.0280.0150.0140.0140.0281.0000.0140.0130.0390.0150.9960.0140.0140.0130.0150.0150.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.9960.0140.0130.0130.0280.0150.0280.0130.3700.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1800.0130.0130.0130.0140.0460.0140.0140.0670.072
passage_of_gases0.2770.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.6270.0130.9420.0130.0460.0130.0580.0580.0130.0130.0450.2380.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0141.0000.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.070
patches_in_throat0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.8820.0260.0270.1180.0120.0090.0790.2220.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.8820.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0121.0000.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
phlegm0.1420.0600.0570.0380.0380.0380.0580.0380.0360.0380.0380.5650.0380.0730.5160.0390.0380.0560.6850.5930.0380.0390.5650.0580.0380.3690.7280.0380.0990.0360.0590.0980.0360.0380.0720.0380.0390.0870.0360.0580.3570.3160.0380.0350.0580.4170.0380.0380.0390.0570.0380.0380.0380.0880.0380.1090.1100.0380.0380.0860.0670.0730.5650.6540.2860.0580.0380.0380.2270.0360.0590.1520.0580.0360.0580.0390.0380.0380.0580.0390.0380.0361.0000.0390.9870.0380.0380.0360.0390.0390.0380.0590.5650.0580.5650.5350.0360.0360.0380.5650.0380.1200.0390.0380.0360.0360.0580.0390.0570.0360.3940.6390.0580.0380.0360.0390.0380.5650.0380.0360.0380.0380.0350.0360.0360.0360.0380.2180.0380.0380.1280.131
polyuria0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.5450.0460.0150.0140.0270.0610.0660.0140.0150.0150.0280.0140.0280.0530.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.4620.0130.0280.0290.1790.0140.0120.0840.0950.0140.0140.9960.0280.0140.0140.9700.0470.0140.0600.0600.0140.0140.4650.0850.0380.0150.0610.0390.0280.0140.0140.0470.0130.0290.0840.0280.0130.6760.0150.0140.0140.0280.0150.0140.0130.0391.0000.9960.0140.0140.0130.0150.0150.0140.0290.0150.6760.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1240.0130.0130.0130.0140.4650.0140.0140.0670.072
prognosis0.9680.9960.9560.9700.9700.9700.9710.9700.9430.9700.9700.9960.9700.9690.9610.9960.9700.9420.9770.9660.9700.9960.9960.9690.9700.9560.9620.9700.9670.9430.9830.9620.9430.9700.9600.9700.9960.9750.9430.9690.9830.9520.9700.9160.9600.9580.9700.9700.9960.9560.9700.9700.9700.9890.9700.9620.9660.9700.9700.9680.9700.9690.9960.9820.9870.9690.9700.9700.9890.9430.9830.9660.9690.9430.9690.9960.9700.9700.9690.9960.9700.9430.9870.9961.0000.9700.9700.9430.9960.9960.9700.9830.9960.9690.9960.9960.9430.9430.9700.9960.9700.9570.9960.9700.9430.9430.9690.9960.9560.9430.9620.9780.9690.9700.9430.9960.9700.9960.9700.9430.9700.9700.9440.9430.9430.9430.9700.9680.9700.9700.9800.965
prominent_veins_on_calf0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.9420.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.9420.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1730.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.6570.0140.0130.0130.0270.0140.0130.0120.0380.0140.9701.0000.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.9130.0140.9420.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
puffy_face_and_eyes0.0760.6770.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.9700.0130.0260.0590.0640.9420.0140.0140.0270.0130.0270.0510.0130.0520.0120.6860.0510.0120.0130.5340.0130.9700.0450.0120.0270.0280.1560.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.4690.0130.0580.0580.0130.0130.4510.0820.0370.0140.0590.0380.6570.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0131.0000.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.9700.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.9420.0450.0130.0130.0650.070
pus_filled_pimples0.0740.0270.0260.0120.0120.0120.0260.0120.8820.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0121.0000.0130.0130.0120.0270.0130.0260.0130.0130.8820.0110.0120.0130.0120.3190.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
receiving_blood_transfusion0.2860.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.0610.0660.0140.0150.0150.0280.0140.0280.0530.0140.4100.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.0840.0950.0140.0140.0150.0280.0140.0140.0140.0470.0140.3700.0600.0140.0140.4650.2650.0380.0150.3850.0390.0280.0140.0140.0470.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.0390.0150.9960.0140.0140.0131.0000.9960.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.9700.3530.309
receiving_unsterile_injections0.2860.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.0610.0660.0140.0150.0150.0280.0140.0280.0530.0140.4100.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.0840.0950.0140.0140.0150.0280.0140.0140.0140.0470.0140.3700.0600.0140.0140.4650.2650.0380.0150.3850.0390.0280.0140.0140.0470.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.0390.0150.9960.0140.0140.0130.9961.0000.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.9700.3530.309
red_sore_around_nose0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.9420.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.1930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0141.0000.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.3290.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.9420.0130.0650.070
red_spots_over_body0.1130.0460.0440.0280.0280.0280.4660.0280.0270.0280.0280.0290.0280.0570.0680.0290.0280.0430.0880.1800.0280.0290.0290.0450.0280.0440.0780.0280.0780.0270.0460.0780.0270.0280.0570.0280.0290.0690.0270.0450.0460.2530.0280.0250.3930.3340.0280.0280.0290.0440.0280.0280.0280.0700.0280.2250.2060.0280.0280.3020.3890.0570.0290.5300.3570.0450.0280.0280.2750.0270.0460.1330.0450.0270.0450.6670.0280.0280.0450.0290.0280.0270.0590.0290.9830.0280.0280.0270.0290.0290.0281.0000.0290.0450.0290.0290.0270.0270.0280.0290.0280.4800.0290.0280.0270.0270.0450.0290.0440.0270.0870.3610.0450.0280.0270.0290.0280.0290.0280.0270.0280.0280.0290.0270.0270.0270.0280.0680.0280.0280.0970.104
redness_of_eyes0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.3870.3360.0140.0150.9960.0280.0140.6860.4120.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.2680.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.0600.0140.0140.0460.0850.0380.9960.3630.0390.0280.0140.0140.4820.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.5650.0150.9960.0140.0140.0130.0150.0150.0140.0291.0000.0280.9960.0150.0130.0130.0140.9960.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.5400.0280.0140.0130.0150.0140.9960.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.0140.0670.072
restlessness0.1110.4590.0430.0270.0270.0270.0440.0270.0260.0270.0270.0280.0270.3480.0670.0280.0270.0430.0870.0950.0270.0280.0280.0440.0270.0430.0760.0270.0770.0260.0450.2470.0260.0270.0560.0270.0280.6430.0260.0440.4390.2490.0270.0250.1190.1350.0270.0270.6760.0430.0270.0270.6570.3000.0270.0860.0860.0270.0270.2880.1200.0570.0280.0870.0580.4460.0270.0270.0690.0260.4660.1190.0440.0260.4460.0280.0270.0270.0440.0280.0270.0260.0580.6760.9690.0270.0270.0260.0280.0280.0270.0450.0281.0000.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0260.0440.0280.0430.0260.2130.0570.0440.0270.0260.0280.0270.0280.0270.0260.0270.0270.1740.0260.0260.0260.0270.6480.0270.0270.0960.103
runny_nose0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.3870.3360.0140.0150.9960.0280.0140.6860.4120.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.2680.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.0600.0140.0140.0460.0850.0380.9960.3630.0390.0280.0140.0140.4820.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.5650.0150.9960.0140.0140.0130.0150.0150.0140.0290.9960.0281.0000.0150.0130.0130.0140.9960.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.5400.0280.0140.0130.0150.0140.9960.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.0140.0670.072
rusty_sputum0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.4680.0150.0140.0270.3870.3360.0140.0150.0150.0280.0140.0280.4120.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.7040.1790.0140.0120.0840.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.0600.0140.0140.0460.0850.0380.0150.3630.0390.0280.0140.0140.0470.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.5350.0150.9960.0140.0140.0130.0150.0150.0140.0290.0150.0280.0151.0000.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.3700.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.0140.0670.072
scurring0.0740.0270.0260.0120.0120.0120.0260.0120.8820.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.8820.0130.0130.0120.0270.0130.0260.0130.0131.0000.0110.0120.0130.0120.3190.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
shivering0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.2930.0120.0130.0130.0260.0120.6060.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0111.0000.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.8820.0110.0110.0120.0430.0120.0120.0630.068
silver_like_dusting0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0270.9420.0130.0130.0460.0130.0580.3580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0121.0000.0140.9420.3290.0140.9420.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
sinus_pressure0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.3870.3360.0140.0150.9960.0280.0140.6860.4120.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.2680.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.0600.0140.0140.0460.0850.0380.9960.3630.0390.0280.0140.0140.4820.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.5650.0150.9960.0140.0140.0130.0150.0150.0140.0290.9960.0280.9960.0150.0130.0130.0141.0000.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.5400.0280.0140.0130.0150.0140.9960.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.0140.0670.072
skin_peeling0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0270.9420.0130.0130.0460.0130.0580.3580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.9420.0141.0000.3290.0140.9420.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
skin_rash0.2240.0960.0920.0640.0640.0640.2030.0640.3190.0640.3290.0660.0640.1170.1370.0660.0640.1650.1760.0250.0640.0660.0660.0940.0640.0920.1550.0640.1560.0620.0950.1550.2960.0640.1160.0640.0660.1390.0620.0940.0950.1040.0640.0600.0510.1160.0640.0640.0660.0920.3290.0640.0640.1410.0640.3170.1700.0640.0640.0650.0470.1170.0660.1730.1080.0940.0640.0640.0580.0620.0950.0890.0940.2960.0940.3390.0640.0640.0940.0660.0640.0620.1200.0660.9570.0640.0640.3190.0660.0660.3290.4800.0660.0940.0660.0660.3190.0620.3290.0660.3291.0000.0660.3290.0620.2960.0940.0660.1600.0620.1730.1110.0940.0640.0620.0660.0640.0660.0640.0620.0640.0640.2240.0620.0620.0620.0640.1380.3290.0640.1930.207
slurred_speech0.0790.0290.0280.0140.0140.9700.0280.0140.0130.0140.0140.0150.0140.5450.0460.0150.0140.0270.0610.0660.0140.0150.0150.0280.0140.0280.0530.0140.0530.0130.0290.0530.0130.0140.0380.9700.0150.4890.0130.0280.0290.1790.0140.0120.2680.0950.0140.0140.0150.0280.0140.0140.0140.4820.0140.0600.0600.0140.0140.0460.0850.0380.0150.0610.0390.0280.0140.0140.0470.0130.0290.2660.0280.0130.0280.0150.0140.0140.0280.9960.0140.0130.0390.0150.9960.0140.0140.0130.0150.0150.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0661.0000.0140.0130.0130.0280.0150.0280.0130.3700.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1800.0130.0130.0130.0140.0460.0140.0140.0670.072
small_dents_in_nails0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.0930.0130.0130.0140.0270.9420.0130.0130.0460.0130.0580.3580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.9420.0140.9420.3290.0141.0000.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
spinning_movements0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.2520.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.5130.0130.0570.0360.0260.0120.0120.0440.0110.0270.2500.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0121.0000.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.9130.0120.1690.0110.0110.0110.0120.0430.0120.0120.0630.068
spotting_ urination0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.6140.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.3480.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.2960.0130.0120.0111.0000.0260.0130.6060.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
stiff_neck0.1110.0450.4530.0270.0270.0270.0440.0270.0260.0270.0270.0280.0270.3480.0670.0280.0270.0430.0870.0950.0270.0280.0280.0440.0270.0430.0760.0270.0770.0260.4390.0760.0260.0270.0560.0270.0280.2850.0260.0440.0450.1760.0270.0250.1250.1350.0270.0270.0280.4530.0270.0270.0270.2800.0270.0860.0860.0270.0270.0670.1200.0570.0280.0870.0580.0440.6570.0270.0690.0260.4390.1190.0440.0260.0440.0280.0270.0270.4460.0280.0270.0260.0580.0280.9690.0270.0270.0260.0280.0280.0270.0450.0280.0440.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0261.0000.0280.0430.0260.0860.0570.4460.0270.0260.0280.0270.0280.0270.0260.0270.6570.1740.0260.0260.0260.0270.0670.0270.0270.0960.103
stomach_bleeding0.3050.0290.0280.9700.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.0610.0660.0140.9960.0150.0280.0140.0280.0530.0140.4100.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.0840.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.3680.0140.0140.0460.2840.0380.0150.0610.0390.0280.0140.0140.0470.0130.0290.2660.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.0390.0150.9960.0140.0140.0130.0150.0150.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0281.0000.0280.0130.0600.0390.0280.0140.0130.0150.0140.0150.0140.0130.0140.0140.1800.0130.0130.0130.0140.0460.0140.0140.3530.309
stomach_pain0.1100.0450.4310.0270.0270.0270.0430.0270.0260.0270.0270.0280.0270.0560.0660.0280.0270.4100.2130.0930.0270.0280.0280.0430.0270.0430.2520.0270.0760.0260.0440.0750.0260.0270.0550.0270.0280.0670.0260.0430.0440.1730.0270.0240.1170.1330.0270.0270.0280.0430.0270.0270.0270.0680.0270.2010.0850.0270.0270.0660.1180.0560.0280.0860.0570.0430.0270.0270.0680.0260.0440.1180.0430.0260.0430.0280.0270.0270.0430.0280.0270.0260.0570.0280.9560.0270.0270.0260.0280.0280.0270.0440.0280.0430.0280.0280.0260.0260.0270.0280.0270.1600.0280.0270.0260.6060.0430.0281.0000.0260.0840.0560.0430.0270.0260.0280.0270.0280.0270.6460.0270.0270.0270.0260.0260.0260.0270.0660.0270.0270.0950.101
sunken_eyes0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.8820.0270.3880.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0261.0000.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1520.0110.0110.0110.0120.0430.0120.0120.0630.068
sweating0.2050.2200.0840.0580.0580.3600.0860.0580.0560.0580.0580.3700.0580.1390.5100.0600.0580.0830.3950.3410.0580.0600.0600.0860.0580.0840.2550.0580.1430.0560.0870.2440.0560.0580.1060.3600.0600.3190.0560.0860.5240.1990.0580.0540.0820.1780.0580.0580.0600.0840.0580.0580.0580.3240.0580.1580.1590.0580.0580.1260.0600.1070.0600.2100.1470.2130.0580.0580.0950.0560.2250.0790.0860.0560.0860.0600.0580.0580.0860.3700.0580.0560.3940.0600.9620.0580.0580.0560.0600.0600.0580.0870.0600.2130.0600.3700.0560.0560.0580.0600.0580.1730.3700.0580.0560.0560.0860.0600.0840.0561.0000.1500.0860.0580.0560.0600.0580.0600.0580.0560.0580.0580.1880.0560.0560.0560.0580.3100.0580.0580.0000.189
swelled_lymph_nodes0.1400.0590.0560.0370.0370.0370.0570.0370.0360.0370.0370.5700.0370.0720.2240.0390.0370.0550.4190.3550.0370.0390.5400.0570.0370.3500.4520.0370.0980.0360.0580.0970.0360.0370.0720.0370.0390.0860.0360.0570.0580.3130.0370.0350.2540.4130.0370.0370.0390.0560.0370.0370.0370.0880.0370.1360.1090.0370.0370.2050.2730.0720.5400.6610.6210.0570.0370.0370.2140.0360.0580.1500.0570.0360.0570.0390.0370.0370.0570.0390.0370.0360.6390.0390.9780.0370.0370.0360.0390.0390.0370.3610.5400.0570.5400.0390.0360.0360.0370.5400.0370.1110.0390.0370.0360.0360.0570.0390.0560.0360.1501.0000.0570.0370.0360.0390.0370.5400.0370.0360.0370.0370.0310.0360.0360.0360.0370.2220.0370.0370.1310.130
swelling_joints0.1110.0450.0430.0270.0270.0270.0440.0270.0260.0270.0270.0280.0270.0570.0670.0280.0270.0430.0870.0950.0270.0280.0280.0440.0270.0430.0760.0270.0770.0260.0450.0760.0260.0270.0560.0270.0280.0680.0260.0440.0450.1760.0270.0250.1190.1350.6570.0270.0280.0430.0270.0270.0270.0690.0270.0860.2110.6570.0270.0670.1200.0570.0280.0870.0580.0440.6570.0270.0690.0260.4390.1190.4460.0260.0440.0280.0270.0270.9420.0280.0270.0260.0580.0280.9690.0270.0270.0260.0280.0280.0270.0450.0280.0440.0280.0280.0260.0260.0270.0280.0270.0940.0280.0270.0260.0260.4460.0280.0430.0260.0860.0571.0000.0270.0260.0280.0270.0280.0270.0260.0270.0270.1740.0260.0260.0260.0270.0670.0270.0270.0960.103
swelling_of_stomach0.2770.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.9420.0360.0130.0140.0450.0120.0270.0280.1220.9420.0100.0810.0930.0130.9420.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0271.0000.0120.0140.0130.0140.0130.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.300
swollen_blood_vessels0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.9130.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.9130.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1670.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.6370.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.9130.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0121.0000.0130.9130.0130.0120.0110.0120.0120.1170.0110.0110.0110.0120.0430.0120.0120.0630.068
swollen_extremeties0.0790.6950.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.9960.0140.0270.0610.0660.9700.0150.0150.0280.0140.0280.0530.0140.0530.0130.7040.0530.0130.0140.5500.0140.9960.0470.0130.0280.0290.1620.0140.0120.0840.0950.0140.0140.0150.0280.0140.0140.0140.4820.0140.0600.0600.0140.0140.4650.0850.0380.0150.0610.0390.6760.0140.0140.0470.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.0390.0150.9960.0140.9700.0130.0150.0150.0140.0290.0150.0280.0150.0150.0130.0130.0140.0150.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.0390.0280.0140.0131.0000.0140.0150.0140.0130.0140.0140.1240.0130.0130.0130.9700.0460.0140.0140.0670.072
swollen_legs0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.9420.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.9420.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1730.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.6570.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.9420.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.9130.0141.0000.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
throat_irritation0.0790.0290.0280.0140.0140.0140.0280.0140.0130.0140.0140.0150.0140.0380.0460.0150.0140.0270.3870.3360.0140.0150.9960.0280.0140.6860.4120.0140.0530.0130.0290.0530.0130.0140.0380.0140.0150.0470.0130.0280.0290.1790.0140.0120.2680.2360.0140.0140.0150.0280.0140.0140.0140.0470.0140.0600.0600.0140.0140.0460.0850.0380.9960.3630.0390.0280.0140.0140.4820.0130.0290.0840.0280.0130.0280.0150.0140.0140.0280.0150.0140.0130.5650.0150.9960.0140.0140.0130.0150.0150.0140.0290.9960.0280.9960.0150.0130.0130.0140.9960.0140.0660.0150.0140.0130.0130.0280.0150.0280.0130.0600.5400.0280.0140.0130.0150.0141.0000.0140.0130.0140.0140.1240.0130.0130.0130.0140.0460.0140.0140.0670.072
toxic_look_(typhos)0.2770.0280.0270.0130.0130.0130.0270.9420.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.3480.0130.0140.0140.6570.0130.0270.0510.0130.0520.0120.0280.4000.0120.0130.0360.0130.0140.0450.0120.0270.0280.1900.0130.0100.2600.2470.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.2580.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0141.0000.0120.0130.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.070
ulcers_on_tongue0.0740.0270.6060.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.3430.0620.0120.0130.0130.0260.0120.0260.3880.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.6460.0110.0560.0360.0260.0120.0110.0130.0120.0130.0121.0000.0120.0120.1520.0110.0110.0110.0120.0430.0120.0120.0630.068
unsteadiness0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.2600.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.5290.0140.0590.0380.0270.0130.0130.0460.0120.0280.2580.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.9130.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0121.0000.0130.1740.0120.0120.0120.0130.0450.0130.0130.0650.070
visual_disturbances0.0760.0280.6660.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.5290.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.6480.0510.0120.0130.0360.0130.0140.4480.0120.0270.0280.1220.0130.0100.2600.0930.0130.0130.0140.6660.0130.0130.0130.4420.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.6570.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0131.0000.1210.0120.0120.0120.0130.0450.0130.0130.0650.070
vomiting0.4790.1790.0120.1740.1580.1740.0470.1740.1170.1210.1210.1800.1210.0380.0390.1240.1210.1690.0540.1430.1210.1800.1240.0340.1210.1720.0000.1210.2730.1520.1770.2610.1170.1740.2150.1740.1240.0920.1170.1740.1770.0000.1740.1140.1980.1140.1210.1740.1240.0270.1210.1740.1210.0980.1210.0550.1990.1210.1210.2540.3140.0380.1240.0590.1440.1740.1210.1210.2130.1170.1770.5240.1740.1170.1740.1800.1210.1210.1740.1800.1740.1170.0350.1240.9440.1210.1210.1170.1240.1240.1210.0290.1240.1740.1240.1240.1170.1170.1210.1240.1210.2240.1800.1210.1690.1170.1740.1800.0270.1520.1880.0310.1740.1740.1170.1240.1210.1240.1740.1520.1740.1211.0000.1170.1170.1520.1210.0530.1210.1210.2690.314
watering_from_eyes0.0740.0270.0260.0120.0120.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.2930.0120.0130.0130.0260.0120.6060.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.8820.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1171.0000.0110.0110.0120.0430.0120.0120.0630.068
weakness_in_limbs0.0740.0270.0260.0120.0120.0120.5970.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.5170.0120.0130.0440.0110.0260.0270.1180.0120.0090.0790.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.5130.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.6370.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1170.0111.0000.0110.0120.0430.0120.0120.0630.068
weakness_of_one_body_side0.0740.0270.0260.0120.9130.0120.0260.0120.0110.0120.0120.0130.0120.0350.0430.0130.0120.0250.0570.0620.0120.0130.0130.0260.0120.0260.0500.0120.0500.0110.0270.0500.0110.0120.0350.0120.0130.0440.0110.0260.0270.1180.0120.0090.2320.0900.0120.0120.0130.0260.0120.0120.0120.0440.0120.0560.0560.0120.0120.0430.0800.0350.0130.0570.0360.0260.0120.0120.0440.0110.0270.0800.0260.0110.0260.0130.0120.0120.0260.0130.0120.0110.0360.0130.9430.0120.0120.0110.0130.0130.0120.0270.0130.0260.0130.0130.0110.0110.0120.0130.0120.0620.0130.0120.0110.0110.0260.0130.0260.0110.0560.0360.0260.0120.0110.0130.0120.0130.0120.0110.0120.0120.1520.0110.0111.0000.0120.0430.0120.0120.0630.068
weight_gain0.0760.6770.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.9700.0130.0260.0590.0640.9420.0140.0140.0270.0130.0270.0510.0130.0520.0120.6860.0510.0120.0130.5340.0130.9700.0450.0120.0270.0280.1560.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.4690.0130.0580.0580.0130.0130.4510.0820.0370.0140.0590.0380.6570.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.9420.0120.0140.0140.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.9700.0130.0140.0130.0120.0130.0130.1210.0120.0120.0121.0000.0450.0130.0130.0650.070
weight_loss0.0150.2970.0660.0450.0450.0450.0670.0450.0430.0450.0450.4650.0450.2080.1590.0460.0450.0650.0980.0620.0450.0460.0460.0670.0450.0660.1210.0450.1190.0430.0680.1210.0430.0450.0840.0450.0460.4150.0430.0670.2820.3620.0450.0420.1740.1390.0450.0450.4650.0660.0450.0450.4510.1650.0450.0900.1270.0450.0450.1570.0000.0850.0460.0960.2180.2880.0450.0450.1020.0430.3020.1750.0670.0430.2880.0460.0450.0450.0670.0460.0450.0430.2180.4650.9680.0450.0450.0430.0460.0460.0450.0680.0460.6480.0460.0460.0430.0430.0450.0460.0450.1380.0460.0450.0430.0430.0670.0460.0660.0430.3100.2220.0670.0450.0430.0460.0450.0460.0450.0430.0450.0450.0530.0430.0430.0430.0451.0000.0450.0450.0700.039
yellow_crust_ooze0.0760.0280.0270.0130.0130.0130.0270.0130.0120.0130.9420.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.0520.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1220.0130.0100.0810.1930.0130.0130.0140.0270.0130.0130.0130.0460.0130.0580.0580.0130.0130.0450.0820.0370.0140.0590.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.0140.0140.9420.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.3290.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0451.0000.0130.0650.070
yellow_urine0.2770.0280.0270.0130.0130.0130.0270.0130.0120.0130.0130.0140.0130.0370.0440.0140.0130.0260.0590.0640.0130.0140.0140.0270.0130.0270.0510.0130.3980.0120.0280.0510.0120.0130.0360.0130.0140.0450.0120.0270.0280.1730.0130.0100.0810.0930.0130.0130.0140.0270.0130.0130.0130.0460.0130.3600.0580.0130.0130.4510.2570.0370.0140.3750.0380.0270.0130.0130.0460.0120.0280.0820.0270.0120.0270.0140.0130.0130.0270.0140.0130.0120.0380.0140.9700.0130.0130.0120.9700.9700.0130.0280.0140.0270.0140.0140.0120.0120.0130.0140.0130.0640.0140.0130.0120.0120.0270.0140.0270.0120.0580.0370.0270.0130.0120.0140.0130.0140.0130.0120.0130.0130.1210.0120.0120.0120.0130.0450.0131.0000.3430.300
yellowing_of_eyes0.5260.0990.0950.3430.0650.0650.0960.0650.0630.0650.0650.3530.0650.1200.0720.0670.0650.0930.0000.0220.0650.3530.0670.0960.0650.0950.0310.0650.6060.0630.0970.0310.0630.0650.1190.0650.0670.1420.0630.1650.0970.2580.0650.0610.2430.0000.0650.0650.0670.0950.0650.0650.0650.1440.0650.1720.3500.0650.0650.0700.7670.1200.0670.1920.3820.0960.0650.0650.0740.0630.0970.4590.0960.0630.0960.0670.0650.0650.0960.0670.0650.0630.1280.0670.9800.0650.0650.0630.3530.3530.0650.0970.0670.0960.0670.0670.0630.0630.0650.0670.0650.1930.0670.0650.0630.0630.0960.3530.0950.0630.0000.1310.0960.0650.0630.0670.0650.0670.0650.0630.0650.0650.2690.0630.0630.0630.0650.0700.0650.3431.0000.715
yellowish_skin0.7320.1060.1010.3000.0700.0700.1030.0700.0680.0700.0700.0720.0700.1290.1500.0720.0700.1000.1920.2090.0700.3090.0720.1030.0700.1010.1700.0700.7090.0680.1040.0000.0680.3000.1270.0700.0720.1520.0680.1620.1040.1940.3000.0660.2600.0400.0700.3000.0720.1010.0700.0700.0700.1540.0700.3000.2970.0700.0700.0390.5430.1290.0720.0190.0960.1030.0700.0700.0430.0680.1040.4050.1030.0680.1030.0720.0700.0700.1030.0720.0700.0680.1310.0720.9650.0700.0700.0680.3090.3090.0700.1040.0720.1030.0720.0720.0680.0680.0700.0720.0700.2070.0720.0700.0680.0680.1030.3090.1010.0680.1890.1300.1030.3000.0680.0720.0700.0720.0700.0680.0700.0700.3140.0680.0680.0680.0700.0390.0700.3000.7151.000

Missing values

2024-01-22T12:00:56.373259image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-22T12:00:56.841827image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosisUnnamed: 133
0111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
1011000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
2101000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
3110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
4111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000Fungal infectionNaN
5011000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
6101000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
7110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
8111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000Fungal infectionNaN
9111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosisUnnamed: 133
4910000000000000001101100100000000000000000000000000000000000000000010000011110000000000000000000001100001000000000000000000000000000000HypothyroidismNaN
4911000000000000001000111000000010000000000010000000000000000010000000000000001000001000000000000000100001000000000000000000000000000000HyperthyroidismNaN
4912000000000001001010000000000010010010000000000000010000000000000000000000001011000000000000000000100000000000000000000000100000000000HypoglycemiaNaN
4913000000100000000000000000000000000000000000000000000000000000000100000000000000110010000000000000000000000000000000000000010000000000OsteoarthristisNaN
4914000000000000000000000000000000000000000000000000000000000000000000000000000000001111000000000000000000000000000000000000010000000000ArthritisNaN
4915000000000001000000000000000000010010000000000000000000000000000000000000000000000000111000000000000000000000000000000000000000000000(vertigo) Paroymsal Positional VertigoNaN
4916010000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001110000000AcneNaN
4917000000000000100000000000000000000000000000000000000000000000000000000000000000000000000001110000000000000000000000000000000000000000Urinary tract infectionNaN
4918010000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001111000PsoriasisNaN
4919010000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000111ImpetigoNaN

Duplicate rows

Most frequently occurring

itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosis# duplicates
7000000000000000000000000000000000000000000000000000000000000000000000000000000001111000000000000000000000000000000000000010000000000Arthritis90
17000000000000000000000000000000000000001000000000000000000001111000000000000000000000000000000000000000000000000000000000000000000000Dimorphic hemmorhoids(piles)90
163000000100000000000000000000000000000000000000000000000000000000100000000000000110010000000000000000000000000000000000000010000000000Osteoarthristis84
252010000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001111000Psoriasis84
22000000000000000000000000000000000000010000000000000000000100000110000000000000000000010000000000000000000000000000000000000000000000Cervical spondylosis78
54000000000000001000000000000000001011000000010000000000000000000000000000000000000000000000000000000000000010000000000000000000000000Hepatitis C78
90000000000000100000000000000000000000000000000000000000000000000000000000000000000000000001110000000000000000000000000000000000000000Urinary tract infection78
100000000000001000000000000000000001000000100000010000000000000000000000000000000000000000000000000000000000000000000011100000000000000Alcoholic hepatitis78
105000000000001000000000000000000010000000000000000000000000000000000000000000000000000000100000000001000000000000000000000000000000000Paralysis (brain hemorrhage)78
110000000000001000000000000000000010010000000000000000000000000000000000000000000000000111000000000000000000000000000000000000000000000(vertigo) Paroymsal Positional Vertigo78